{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "7ce78fce0aa14620a60fa553c97ee723": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_f8ab6683e0a54815a3d046a6e58f632c", "IPY_MODEL_c248c1f8fa0c4d5eac09aaa33a96ee5e", "IPY_MODEL_2a16b1fe34dd4048984f8e8aa8f3c2a5" ], "layout": "IPY_MODEL_05a5f598e0a74dfd8ad8b58c0cbde79b" } }, "f8ab6683e0a54815a3d046a6e58f632c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_433452b427e340ccbd845b42a6e7b242", "placeholder": "​", "style": "IPY_MODEL_00570ed4b9c444a2bb2462ccbc5fb288", "value": "Uploading the dataset shards: 100%" } }, "c248c1f8fa0c4d5eac09aaa33a96ee5e": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b3115523544648ecaed834b83cbed5d9", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_1c0bc022b6a341d7aeecc2fc8381a5af", "value": 1 } }, "2a16b1fe34dd4048984f8e8aa8f3c2a5": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2b60380ca15c49cbbefa69339ef3ab6a", "placeholder": "​", "style": "IPY_MODEL_f37c9e5a5e8c4462b37108bd6ab839eb", "value": " 1/1 [00:01<00:00,  1.29s/it]" } }, "05a5f598e0a74dfd8ad8b58c0cbde79b": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "433452b427e340ccbd845b42a6e7b242": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "00570ed4b9c444a2bb2462ccbc5fb288": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "b3115523544648ecaed834b83cbed5d9": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "1c0bc022b6a341d7aeecc2fc8381a5af": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "2b60380ca15c49cbbefa69339ef3ab6a": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "f37c9e5a5e8c4462b37108bd6ab839eb": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "aa0db46a83e24d178cbb895aa75d64f1": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_33bc7d72ed38408883ace782a06925f5", "IPY_MODEL_85566cfa2ec94299892122ff510d03a3", "IPY_MODEL_afffea43fb674d5a8914f0f8e4eafe54" ], "layout": "IPY_MODEL_c339898d18fa4e26a8ee4f1c6a65f852" } }, "33bc7d72ed38408883ace782a06925f5": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6152e5539ecc4f1da06b2af7b0d089fe", "placeholder": "​", "style": "IPY_MODEL_9d9ed88968554aea896a58803d4027d3", "value": "Creating parquet from Arrow format: 100%" } }, "85566cfa2ec94299892122ff510d03a3": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9076d4ac0d8e421a89126b55dcd96bb1", "max": 3, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_d9177d1445134cfa86f8073e1eb18ce0", "value": 3 } }, "afffea43fb674d5a8914f0f8e4eafe54": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ffe646ebf5eb48f18459060a41476080", "placeholder": "​", "style": "IPY_MODEL_d4ad33fa22974e8cb667de54fc6fdc1b", "value": " 3/3 [00:00<00:00, 74.31ba/s]" } }, "c339898d18fa4e26a8ee4f1c6a65f852": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "6152e5539ecc4f1da06b2af7b0d089fe": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "9d9ed88968554aea896a58803d4027d3": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "9076d4ac0d8e421a89126b55dcd96bb1": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "d9177d1445134cfa86f8073e1eb18ce0": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "ffe646ebf5eb48f18459060a41476080": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "d4ad33fa22974e8cb667de54fc6fdc1b": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "bd2c2d08157244bda13921d6516d61ad": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_f85e71053b1f49e6ba271e8205956a49", "IPY_MODEL_2242388fb33d4b20a52f3182ee6438b4", "IPY_MODEL_78c262c3e9af47099fc9684904a8bffb" ], "layout": "IPY_MODEL_16c674864afc4c278c409801e8697c9e" } }, "f85e71053b1f49e6ba271e8205956a49": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_49e239afd0ee405e8f54f1dbf4848d56", "placeholder": "​", "style": "IPY_MODEL_d5ca61aca1ea49e195bf6b65c159b813", "value": "Uploading the dataset shards: 100%" } }, "2242388fb33d4b20a52f3182ee6438b4": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a77579e50bad44e89064e20b77f6d9c8", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_6a409e74995244649c92dd7acbeb3f50", "value": 1 } }, "78c262c3e9af47099fc9684904a8bffb": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1b0baac01b894dd9b4bf0b2c0a9740ed", "placeholder": "​", "style": "IPY_MODEL_37999fd948e642c2af98e6020327d082", "value": " 1/1 [00:01<00:00,  1.46s/it]" } }, "16c674864afc4c278c409801e8697c9e": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "49e239afd0ee405e8f54f1dbf4848d56": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "d5ca61aca1ea49e195bf6b65c159b813": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "a77579e50bad44e89064e20b77f6d9c8": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "6a409e74995244649c92dd7acbeb3f50": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "1b0baac01b894dd9b4bf0b2c0a9740ed": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "37999fd948e642c2af98e6020327d082": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "0cff935ffb2743b6bed569a4f4f393e0": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_c6d65efc78cf473b990daf11159dd4c0", "IPY_MODEL_ac544844e3964f4bba14b195b69e5406", "IPY_MODEL_dd4c910baed347a39b7ffc94b0ffc856" ], "layout": "IPY_MODEL_768c17c8f789489b9952de7593d30705" } }, "c6d65efc78cf473b990daf11159dd4c0": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_fc3e5772486c42859973f3e25ee2d828", "placeholder": "​", "style": "IPY_MODEL_12a568bb8133479e9f84791660b335c3", "value": "Creating parquet from Arrow format: 100%" } }, "ac544844e3964f4bba14b195b69e5406": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4734681a45f549e79e09eb9b5e4b0f9b", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_c6bfefed0f1e49e4aff202c484bded0a", "value": 1 } }, "dd4c910baed347a39b7ffc94b0ffc856": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_76d86e530c2248b69f1e1a9306ee37d2", "placeholder": "​", "style": "IPY_MODEL_fa9cd5e2cd6d4560afe96dc3df3ee595", "value": " 1/1 [00:00<00:00, 48.59ba/s]" } }, "768c17c8f789489b9952de7593d30705": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "fc3e5772486c42859973f3e25ee2d828": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "12a568bb8133479e9f84791660b335c3": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "4734681a45f549e79e09eb9b5e4b0f9b": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "c6bfefed0f1e49e4aff202c484bded0a": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "76d86e530c2248b69f1e1a9306ee37d2": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "fa9cd5e2cd6d4560afe96dc3df3ee595": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "5995e30272f246bdb82c4c018145e6ed": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_ee93dc8e5e5243af8fcd58b7f8f406ce", "IPY_MODEL_52bc3f36e6e2416c8c3286cadd8f108d", "IPY_MODEL_17bbdb14f1db4a329d2fd6529d19876b" ], "layout": "IPY_MODEL_c0607941f0284eb3ba36ed2c12795d3a" } }, "ee93dc8e5e5243af8fcd58b7f8f406ce": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a57742af98a04da2968413cea64fd023", "placeholder": "​", "style": "IPY_MODEL_4fec072ec1344f5886b5016dd614be32", "value": "Uploading the dataset shards: 100%" } }, "52bc3f36e6e2416c8c3286cadd8f108d": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_10d444226a4240c088f0e97e28c27e4a", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_ba81b8435d214280ba6305dbee60c70d", "value": 1 } }, "17bbdb14f1db4a329d2fd6529d19876b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_405f047617c346808b18452a1318d14b", "placeholder": "​", "style": "IPY_MODEL_ad90f1ef273c4dda8cf35108a13cdf6d", "value": " 1/1 [00:00<00:00,  1.01it/s]" } }, "c0607941f0284eb3ba36ed2c12795d3a": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "a57742af98a04da2968413cea64fd023": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "4fec072ec1344f5886b5016dd614be32": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "10d444226a4240c088f0e97e28c27e4a": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ba81b8435d214280ba6305dbee60c70d": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "405f047617c346808b18452a1318d14b": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ad90f1ef273c4dda8cf35108a13cdf6d": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "7ede365033a746ba83be95a8043ff54c": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_c2f32106ce304990b6f2454da926d913", "IPY_MODEL_a93706f5106045ccbd04397d450d84af", "IPY_MODEL_a59b5b2541a846669119dc986df5e5f1" ], "layout": "IPY_MODEL_f60abed2dd6541c283c1702c0ac83b2a" } }, "c2f32106ce304990b6f2454da926d913": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_392b4a60fc2e408f90d00e88465b0b47", "placeholder": "​", "style": "IPY_MODEL_45ab552de57d49d3b541f1eb975306d6", "value": "Creating parquet from Arrow format: 100%" } }, "a93706f5106045ccbd04397d450d84af": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4107196d970446149cf32a8ea8a9452e", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_e6b535c3023249f8b3640f33ffd2adb1", "value": 1 } }, "a59b5b2541a846669119dc986df5e5f1": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_63a2f91de2c246fea86c831c5fd03e4f", "placeholder": "​", "style": "IPY_MODEL_ec8641b65d664be8999f80a8a575b01e", "value": " 1/1 [00:00<00:00, 46.25ba/s]" } }, "f60abed2dd6541c283c1702c0ac83b2a": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "392b4a60fc2e408f90d00e88465b0b47": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "45ab552de57d49d3b541f1eb975306d6": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "4107196d970446149cf32a8ea8a9452e": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "e6b535c3023249f8b3640f33ffd2adb1": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "63a2f91de2c246fea86c831c5fd03e4f": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ec8641b65d664be8999f80a8a575b01e": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } } } } }, "cells": [ { "cell_type": "code", "execution_count": 6, "metadata": { "id": "9LrNllwDhJa3" }, "outputs": [], "source": [ "import pandas as pd\n", "\n", "df_corpus = pd.read_json(\"hf://datasets/mteb/quora/corpus.jsonl\", lines=True)\n", "\n", "df_queries = pd.read_json(\"hf://datasets/mteb/quora/queries.jsonl\", lines=True)\n", "\n", "splits = {'dev': 'qrels/dev.jsonl', 'test': 'qrels/test.jsonl'}\n", "df_qrels_dev = pd.read_json(\"hf://datasets/mteb/quora/\" + splits[\"dev\"], lines=True)\n", "df_qrels_test = pd.read_json(\"hf://datasets/mteb/quora/\" + splits[\"test\"], lines=True)" ] }, { "cell_type": "markdown", "source": [ "## 数据集分析" ], "metadata": { "id": "IPAFU4S7iZVR" } }, { "cell_type": "code", "source": [ "df_queries" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 423 }, "id": "CCCjxOkyid8T", "outputId": "3d2d4b4e-815a-405f-b407-b5ae7f42ebcb" }, "execution_count": 7, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " _id text\n", "0 318 How does Quora look to a moderator?\n", "1 378 How do I refuse to chose between different thi...\n", "2 379 Did Ben Affleck shine more than Christian Bale...\n", "3 399 What are the effects of demonitization of 500 ...\n", "4 420 Why creativity is important?\n", "... ... ...\n", "14995 537630 How can I drink 12 beers as fast as possible w...\n", "14996 537660 How did different races come about?\n", "14997 537730 How do I get more friends on Facebook?\n", "14998 537793 Can I take my 14 year old son to the Global Ci...\n", "14999 537876 How do Russian politics and geostrategy affect...\n", "\n", "[15000 rows x 2 columns]" ], "text/html": [ "\n", "
\n", "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
_idtext
0318How does Quora look to a moderator?
1378How do I refuse to chose between different thi...
2379Did Ben Affleck shine more than Christian Bale...
3399What are the effects of demonitization of 500 ...
4420Why creativity is important?
.........
14995537630How can I drink 12 beers as fast as possible w...
14996537660How did different races come about?
14997537730How do I get more friends on Facebook?
14998537793Can I take my 14 year old son to the Global Ci...
14999537876How do Russian politics and geostrategy affect...
\n", "

15000 rows × 2 columns

\n", "
\n", "
\n", "\n", "
\n", " \n", "\n", " \n", "\n", " \n", "
\n", "\n", "\n", "
\n", " \n", "\n", "\n", "\n", " \n", "
\n", "\n", "
\n", " \n", " \n", " \n", "
\n", "\n", "
\n", "
\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df_queries", "summary": "{\n \"name\": \"df_queries\",\n \"rows\": 15000,\n \"fields\": [\n {\n \"column\": \"_id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 154103,\n \"min\": 46,\n \"max\": 537876,\n \"num_unique_values\": 15000,\n \"samples\": [\n 332773,\n 72667,\n 429512\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"text\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 14998,\n \"samples\": [\n \"What is the best way to prepare for JEE?\",\n \"Do venture capitalists or angel investors invest in projects of part-time entrepreneurs who have a good business plan and idea?\",\n \"What are the dangers/benefits of the legalization of marijuana?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 7 } ] }, { "cell_type": "code", "source": [ "df_qrels_test" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 423 }, "id": "dEFuGK6mipeG", "outputId": "5b21a497-434f-47b7-996e-4dfd66025ae1" }, "execution_count": 17, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " query-id corpus-id score\n", "0 46 134031 1\n", "1 46 271267 1\n", "2 46 134030 1\n", "3 187 144864 1\n", "4 187 202157 1\n", "... ... ... ...\n", "15670 537630 537629 1\n", "15671 537660 537661 1\n", "15672 537730 537729 1\n", "15673 537793 537792 1\n", "15674 537876 537875 1\n", "\n", "[15675 rows x 3 columns]" ], "text/html": [ "\n", "
\n", "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
query-idcorpus-idscore
0461340311
1462712671
2461340301
31871448641
41872021571
............
156705376305376291
156715376605376611
156725377305377291
156735377935377921
156745378765378751
\n", "

15675 rows × 3 columns

\n", "
\n", "
\n", "\n", "
\n", " \n", "\n", " \n", "\n", " \n", "
\n", "\n", "\n", "
\n", " \n", "\n", "\n", "\n", " \n", "
\n", "\n", "
\n", " \n", " \n", " \n", "
\n", "\n", "
\n", "
\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df_qrels_test", "summary": "{\n \"name\": \"df_qrels_test\",\n \"rows\": 15675,\n \"fields\": [\n {\n \"column\": \"query-id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 154705,\n \"min\": 46,\n \"max\": 537876,\n \"num_unique_values\": 10000,\n \"samples\": [\n 319838,\n 236489,\n 84565\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"corpus-id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 154095,\n \"min\": 37,\n \"max\": 537875,\n \"num_unique_values\": 15675,\n \"samples\": [\n 409674,\n 310735,\n 21579\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"score\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 1,\n \"num_unique_values\": 1,\n \"samples\": [\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 17 } ] }, { "cell_type": "code", "source": [ "df_corpus" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 423 }, "id": "mz3tEjZ3QpgO", "outputId": "4300036d-db9d-4e37-e098-681cfb6ea5fb" }, "execution_count": 30, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " _id title text\n", "0 1 What is the step by step guide to invest in sh...\n", "1 2 What is the step by step guide to invest in sh...\n", "2 3 What is the story of Kohinoor (Koh-i-Noor) Dia...\n", "3 4 What would happen if the Indian government sto...\n", "4 5 How can I increase the speed of my internet co...\n", "... ... ... ...\n", "522926 537929 What's this coin?\n", "522927 537930 What is the approx annual cost of living while...\n", "522928 537931 I am having little hairfall problem but I want...\n", "522929 537932 What is like to have sex with cousin?\n", "522930 537933 What is it like to have sex with your cousin?\n", "\n", "[522931 rows x 3 columns]" ], "text/html": [ "\n", "
\n", "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
_idtitletext
01What is the step by step guide to invest in sh...
12What is the step by step guide to invest in sh...
23What is the story of Kohinoor (Koh-i-Noor) Dia...
34What would happen if the Indian government sto...
45How can I increase the speed of my internet co...
............
522926537929What's this coin?
522927537930What is the approx annual cost of living while...
522928537931I am having little hairfall problem but I want...
522929537932What is like to have sex with cousin?
522930537933What is it like to have sex with your cousin?
\n", "

522931 rows × 3 columns

\n", "
\n", "
\n", "\n", "
\n", " \n", "\n", " \n", "\n", " \n", "
\n", "\n", "\n", "
\n", " \n", "\n", "\n", "\n", " \n", "
\n", "\n", "
\n", " \n", " \n", " \n", "
\n", "\n", "
\n", "
\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df_corpus" } }, "metadata": {}, "execution_count": 30 } ] }, { "cell_type": "code", "source": [ "df_qrels_test['score'].value_counts()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 147 }, "id": "6PhasTLYir_2", "outputId": "cdc419f8-cdfc-4b78-dc59-6f5a11fd8703" }, "execution_count": 22, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "score\n", "1 15675\n", "Name: count, dtype: int64" ], "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
count
score
115675
\n", "

" ] }, "metadata": {}, "execution_count": 22 } ] }, { "cell_type": "code", "source": [ "df_qrels_dev['query-id'].value_counts()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 489 }, "id": "GrQ3MtOYiygq", "outputId": "f2c73317-63d4-4e2e-b93d-76956803aab0" }, "execution_count": 11, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "query-id\n", "80779 84\n", "11167 50\n", "106721 34\n", "399 28\n", "12508 24\n", " ..\n", "1166 1\n", "975 1\n", "548 1\n", "420 1\n", "378 1\n", "Name: count, Length: 5000, dtype: int64" ], "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
count
query-id
8077984
1116750
10672134
39928
1250824
......
11661
9751
5481
4201
3781
\n", "

5000 rows × 1 columns

\n", "

" ] }, "metadata": {}, "execution_count": 11 } ] }, { "cell_type": "code", "source": [ "df_qrels = pd.concat([df_qrels_dev, df_qrels_test])\n", "df_qrels" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 423 }, "id": "s16kit8GPE8r", "outputId": "d8278912-958b-4655-abc0-436823a65e76" }, "execution_count": 25, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " query-id corpus-id score\n", "0 318 317 1\n", "1 378 377 1\n", "2 379 29976 1\n", "3 379 380 1\n", "4 379 45646 1\n", "... ... ... ...\n", "15670 537630 537629 1\n", "15671 537660 537661 1\n", "15672 537730 537729 1\n", "15673 537793 537792 1\n", "15674 537876 537875 1\n", "\n", "[23301 rows x 3 columns]" ], "text/html": [ "\n", "
\n", "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
query-idcorpus-idscore
03183171
13783771
2379299761
33793801
4379456461
............
156705376305376291
156715376605376611
156725377305377291
156735377935377921
156745378765378751
\n", "

23301 rows × 3 columns

\n", "
\n", "
\n", "\n", "
\n", " \n", "\n", " \n", "\n", " \n", "
\n", "\n", "\n", "
\n", " \n", "\n", "\n", "\n", " \n", "
\n", "\n", "
\n", " \n", " \n", " \n", "
\n", "\n", "
\n", "
\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df_qrels", "summary": "{\n \"name\": \"df_qrels\",\n \"rows\": 23301,\n \"fields\": [\n {\n \"column\": \"query-id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 154059,\n \"min\": 46,\n \"max\": 537876,\n \"num_unique_values\": 15000,\n \"samples\": [\n 332773,\n 72667,\n 429512\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"corpus-id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 154052,\n \"min\": 37,\n \"max\": 537894,\n \"num_unique_values\": 23301,\n \"samples\": [\n 289980,\n 127084,\n 511122\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"score\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 1,\n \"num_unique_values\": 1,\n \"samples\": [\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 25 } ] }, { "cell_type": "markdown", "source": [ "## 数据集处理" ], "metadata": { "id": "-1TuL-mQi_uY" } }, { "cell_type": "markdown", "source": [ "### 分组方案一\n", "- query当作条件\n", "- 第二个参数叫group,存放所有的相似句子对\n", "\n", "一共会产出?条数据" ], "metadata": { "id": "9H64ohzzjCoD" } }, { "cell_type": "code", "source": [ "df_corpus_rn = df_corpus[['_id', 'text']].rename(columns={\"_id\": \"corpus-id\",\"text\": \"corpus\"})\n", "print(df_corpus_rn)\n", "df_queries_rn = df_queries[['_id', 'text']].rename(columns={\"_id\": \"query-id\",\"text\": \"query\"})\n", "print(df_queries_rn)\n", "\n", "df__qerl_final = df_qrels.merge(df_corpus_rn, on='corpus-id').merge(df_queries_rn, on='query-id')\n", "df__qerl_final" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 932 }, "id": "xztPzEuTQQlV", "outputId": "f69d814d-7177-4dff-93e0-d2bdd90702eb" }, "execution_count": 37, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ " corpus-id corpus\n", "0 1 What is the step by step guide to invest in sh...\n", "1 2 What is the step by step guide to invest in sh...\n", "2 3 What is the story of Kohinoor (Koh-i-Noor) Dia...\n", "3 4 What would happen if the Indian government sto...\n", "4 5 How can I increase the speed of my internet co...\n", "... ... ...\n", "522926 537929 What's this coin?\n", "522927 537930 What is the approx annual cost of living while...\n", "522928 537931 I am having little hairfall problem but I want...\n", "522929 537932 What is like to have sex with cousin?\n", "522930 537933 What is it like to have sex with your cousin?\n", "\n", "[522931 rows x 2 columns]\n", " query-id query\n", "0 318 How does Quora look to a moderator?\n", "1 378 How do I refuse to chose between different thi...\n", "2 379 Did Ben Affleck shine more than Christian Bale...\n", "3 399 What are the effects of demonitization of 500 ...\n", "4 420 Why creativity is important?\n", "... ... ...\n", "14995 537630 How can I drink 12 beers as fast as possible w...\n", "14996 537660 How did different races come about?\n", "14997 537730 How do I get more friends on Facebook?\n", "14998 537793 Can I take my 14 year old son to the Global Ci...\n", "14999 537876 How do Russian politics and geostrategy affect...\n", "\n", "[15000 rows x 2 columns]\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " query-id corpus-id score \\\n", "0 318 317 1 \n", "1 378 377 1 \n", "2 379 29976 1 \n", "3 379 380 1 \n", "4 379 45646 1 \n", "... ... ... ... \n", "23296 537630 537629 1 \n", "23297 537660 537661 1 \n", "23298 537730 537729 1 \n", "23299 537793 537792 1 \n", "23300 537876 537875 1 \n", "\n", " corpus \\\n", "0 What does the Quora website look like to membe... \n", "1 Is it possible to pursue many different things... \n", "2 According to you, whose Batman performance was... \n", "3 No fanboys please, but who was the true batman... \n", "4 Who do you think portrayed Batman better: Chri... \n", "... ... \n", "23296 How can I drink 12 beers as fast as possible w... \n", "23297 How did humans turn into different races of pe... \n", "23298 How can someone get more Facebook friends? \n", "23299 Can I take my 14 year old son to the Global Ci... \n", "23300 How does Russian politics affect Australia and... \n", "\n", " query \n", "0 How does Quora look to a moderator? \n", "1 How do I refuse to chose between different thi... \n", "2 Did Ben Affleck shine more than Christian Bale... \n", "3 Did Ben Affleck shine more than Christian Bale... \n", "4 Did Ben Affleck shine more than Christian Bale... \n", "... ... \n", "23296 How can I drink 12 beers as fast as possible w... \n", "23297 How did different races come about? \n", "23298 How do I get more friends on Facebook? \n", "23299 Can I take my 14 year old son to the Global Ci... \n", "23300 How do Russian politics and geostrategy affect... \n", "\n", "[23301 rows x 5 columns]" ], "text/html": [ "\n", "
\n", "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
query-idcorpus-idscorecorpusquery
03183171What does the Quora website look like to membe...How does Quora look to a moderator?
13783771Is it possible to pursue many different things...How do I refuse to chose between different thi...
2379299761According to you, whose Batman performance was...Did Ben Affleck shine more than Christian Bale...
33793801No fanboys please, but who was the true batman...Did Ben Affleck shine more than Christian Bale...
4379456461Who do you think portrayed Batman better: Chri...Did Ben Affleck shine more than Christian Bale...
..................
232965376305376291How can I drink 12 beers as fast as possible w...How can I drink 12 beers as fast as possible w...
232975376605376611How did humans turn into different races of pe...How did different races come about?
232985377305377291How can someone get more Facebook friends?How do I get more friends on Facebook?
232995377935377921Can I take my 14 year old son to the Global Ci...Can I take my 14 year old son to the Global Ci...
233005378765378751How does Russian politics affect Australia and...How do Russian politics and geostrategy affect...
\n", "

23301 rows × 5 columns

\n", "
\n", "
\n", "\n", "
\n", " \n", "\n", " \n", "\n", " \n", "
\n", "\n", "\n", "
\n", " \n", "\n", "\n", "\n", " \n", "
\n", "\n", "
\n", " \n", " \n", " \n", "
\n", "\n", "
\n", "
\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df__qerl_final", "summary": "{\n \"name\": \"df__qerl_final\",\n \"rows\": 23301,\n \"fields\": [\n {\n \"column\": \"query-id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 154059,\n \"min\": 46,\n \"max\": 537876,\n \"num_unique_values\": 15000,\n \"samples\": [\n 332773,\n 72667,\n 429512\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"corpus-id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 154052,\n \"min\": 37,\n \"max\": 537894,\n \"num_unique_values\": 23301,\n \"samples\": [\n 289980,\n 127084,\n 511122\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"score\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 1,\n \"num_unique_values\": 1,\n \"samples\": [\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"corpus\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 23298,\n \"samples\": [\n \"I want learn Chinese?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"query\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 14998,\n \"samples\": [\n \"What is the best way to prepare for JEE?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 37 } ] }, { "cell_type": "code", "source": [ "name_group_list = [(name[0], group) for name, group in df__qerl_final.groupby(['query-id'])]\n", "print(len(name_group_list))\n", "print(len(name_group_list[0][1]))\n", "print(name_group_list[1][1])\n", "print(len(name_group_list[1][1]))\n", "\n", "print()\n", "\n", "name_group_list_filter = list(filter(lambda _: len(_[1]) > 1, name_group_list))\n", "print(len(name_group_list_filter))\n", "print(len(name_group_list_filter[0][1]))\n", "print(name_group_list_filter[1][1])\n", "print(len(name_group_list_filter[1][1]))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "fqt3Ar9YjQRS", "outputId": "fef185bf-7d6b-40b1-b681-2fbca5b26b5a" }, "execution_count": 39, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "15000\n", "3\n", " query-id corpus-id score \\\n", "7629 187 144864 1 \n", "7630 187 202157 1 \n", "7631 187 68733 1 \n", "7632 187 68732 1 \n", "7633 187 394711 1 \n", "7634 187 394712 1 \n", "7635 187 188 1 \n", "\n", " corpus \\\n", "7629 Why do I have nightmares? \n", "7630 Why do we get Nightmares? \n", "7631 What are the main causes of nightmares? \n", "7632 Why do we have nightmares? What is the cause o... \n", "7633 What do you think causes bad dreams? \n", "7634 Why do we have bad dreams? \n", "7635 What causes nightmares that seem real? \n", "\n", " query \n", "7629 What causes a nightmare? \n", "7630 What causes a nightmare? \n", "7631 What causes a nightmare? \n", "7632 What causes a nightmare? \n", "7633 What causes a nightmare? \n", "7634 What causes a nightmare? \n", "7635 What causes a nightmare? \n", "7\n", "\n", "3449\n", "3\n", " query-id corpus-id score \\\n", "7629 187 144864 1 \n", "7630 187 202157 1 \n", "7631 187 68733 1 \n", "7632 187 68732 1 \n", "7633 187 394711 1 \n", "7634 187 394712 1 \n", "7635 187 188 1 \n", "\n", " corpus \\\n", "7629 Why do I have nightmares? \n", "7630 Why do we get Nightmares? \n", "7631 What are the main causes of nightmares? \n", "7632 Why do we have nightmares? What is the cause o... \n", "7633 What do you think causes bad dreams? \n", "7634 Why do we have bad dreams? \n", "7635 What causes nightmares that seem real? \n", "\n", " query \n", "7629 What causes a nightmare? \n", "7630 What causes a nightmare? \n", "7631 What causes a nightmare? \n", "7632 What causes a nightmare? \n", "7633 What causes a nightmare? \n", "7634 What causes a nightmare? \n", "7635 What causes a nightmare? \n", "7\n" ] } ] }, { "cell_type": "code", "source": [ "\n", "print(name_group_list_filter[1])" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "aDdHoaLuPqNv", "outputId": "010f849d-6da5-4e4d-cd01-c95f628b8ae6" }, "execution_count": 40, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(187, query-id corpus-id score \\\n", "7629 187 144864 1 \n", "7630 187 202157 1 \n", "7631 187 68733 1 \n", "7632 187 68732 1 \n", "7633 187 394711 1 \n", "7634 187 394712 1 \n", "7635 187 188 1 \n", "\n", " corpus \\\n", "7629 Why do I have nightmares? \n", "7630 Why do we get Nightmares? \n", "7631 What are the main causes of nightmares? \n", "7632 Why do we have nightmares? What is the cause o... \n", "7633 What do you think causes bad dreams? \n", "7634 Why do we have bad dreams? \n", "7635 What causes nightmares that seem real? \n", "\n", " query \n", "7629 What causes a nightmare? \n", "7630 What causes a nightmare? \n", "7631 What causes a nightmare? \n", "7632 What causes a nightmare? \n", "7633 What causes a nightmare? \n", "7634 What causes a nightmare? \n", "7635 What causes a nightmare? )\n" ] } ] }, { "cell_type": "code", "source": [ "name_group_list_filter[0][1]['corpus'].tolist()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1Z069tvwTjGx", "outputId": "7be20304-7b68-45bc-8797-e6a0867b848f" }, "execution_count": 45, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "['What are good questions to ask on Quora?',\n", " 'Why should I ask Quora?',\n", " \"What's the best question to ask in Quora?\"]" ] }, "metadata": {}, "execution_count": 45 } ] }, { "cell_type": "code", "source": [ "def handle(row):\n", " # query_id = row[0]\n", " cond = row[1]['query'].tolist()[0]\n", " group = row[1]['corpus'].tolist()\n", " return (cond, group)\n", "\n", "\n", "# print(handle({\"_id\":\"dev_query1\", \"text\":\"生产过后怎么还有一层肚子\"}))\n" ], "metadata": { "id": "AUsrAjm1kEyP" }, "execution_count": 47, "outputs": [] }, { "cell_type": "code", "source": [ "result = list(map(handle, name_group_list_filter))" ], "metadata": { "id": "Dukd3NpYkWvh" }, "execution_count": 48, "outputs": [] }, { "cell_type": "code", "source": [ "result_df = pd.DataFrame(result, columns=['condition', 'group'])\n", "result_df" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 423 }, "id": "4G-HkzOzknsE", "outputId": "daf69d64-e95e-425c-a7c8-a079cc80405d" }, "execution_count": 50, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " condition \\\n", "0 Which question should I ask on Quora? \n", "1 What causes a nightmare? \n", "2 If I do not monetize YouTube videos & upload c... \n", "3 Did Ben Affleck shine more than Christian Bale... \n", "4 What are the effects of demonitization of 500 ... \n", "... ... \n", "3444 Who invented the bra? \n", "3445 What are the ways that India and Pakistan can ... \n", "3446 Can the president replace the vice president w... \n", "3447 Why do golf Ball have dimple? \n", "3448 What is natural selection? Why does it occur? \n", "\n", " group \n", "0 [What are good questions to ask on Quora?, Why... \n", "1 [Why do I have nightmares?, Why do we get Nigh... \n", "2 [Can I upload part of anime videos on YouTube ... \n", "3 [According to you, whose Batman performance wa... \n", "4 [How does demonetization of the 500 and 1000 n... \n", "... ... \n", "3444 [When and why was bra invented?, When was the ... \n", "3445 [How can there be everlasting peace between In... \n", "3446 [Can the President fire the Vice President?, C... \n", "3447 [Why do regulation golf balls have dimples?, W... \n", "3448 [What are the best ways to explain evolution b... \n", "\n", "[3449 rows x 2 columns]" ], "text/html": [ "\n", "
\n", "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
conditiongroup
0Which question should I ask on Quora?[What are good questions to ask on Quora?, Why...
1What causes a nightmare?[Why do I have nightmares?, Why do we get Nigh...
2If I do not monetize YouTube videos & upload c...[Can I upload part of anime videos on YouTube ...
3Did Ben Affleck shine more than Christian Bale...[According to you, whose Batman performance wa...
4What are the effects of demonitization of 500 ...[How does demonetization of the 500 and 1000 n...
.........
3444Who invented the bra?[When and why was bra invented?, When was the ...
3445What are the ways that India and Pakistan can ...[How can there be everlasting peace between In...
3446Can the president replace the vice president w...[Can the President fire the Vice President?, C...
3447Why do golf Ball have dimple?[Why do regulation golf balls have dimples?, W...
3448What is natural selection? Why does it occur?[What are the best ways to explain evolution b...
\n", "

3449 rows × 2 columns

\n", "
\n", "
\n", "\n", "
\n", " \n", "\n", " \n", "\n", " \n", "
\n", "\n", "\n", "
\n", " \n", "\n", "\n", "\n", " \n", "
\n", "\n", "
\n", " \n", " \n", " \n", "
\n", "\n", "
\n", "
\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "result_df", "summary": "{\n \"name\": \"result_df\",\n \"rows\": 3449,\n \"fields\": [\n {\n \"column\": \"condition\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 3449,\n \"samples\": [\n \"What are the best bank exam books?\",\n \"How do I unpop a clogged ear?\",\n \"What are some common examples of renewable resources?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"group\",\n \"properties\": {\n \"dtype\": \"object\",\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 50 } ] }, { "cell_type": "code", "source": [ "result_df = result_df.dropna()\n", "result_df" ], "metadata": { "id": "BUewuga8TTWH", "colab": { "base_uri": "https://localhost:8080/", "height": 423 }, "outputId": "e5e3b639-0fde-4def-a15b-cf6a58523ab6" }, "execution_count": 51, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " condition \\\n", "0 Which question should I ask on Quora? \n", "1 What causes a nightmare? \n", "2 If I do not monetize YouTube videos & upload c... \n", "3 Did Ben Affleck shine more than Christian Bale... \n", "4 What are the effects of demonitization of 500 ... \n", "... ... \n", "3444 Who invented the bra? \n", "3445 What are the ways that India and Pakistan can ... \n", "3446 Can the president replace the vice president w... \n", "3447 Why do golf Ball have dimple? \n", "3448 What is natural selection? Why does it occur? \n", "\n", " group \n", "0 [What are good questions to ask on Quora?, Why... \n", "1 [Why do I have nightmares?, Why do we get Nigh... \n", "2 [Can I upload part of anime videos on YouTube ... \n", "3 [According to you, whose Batman performance wa... \n", "4 [How does demonetization of the 500 and 1000 n... \n", "... ... \n", "3444 [When and why was bra invented?, When was the ... \n", "3445 [How can there be everlasting peace between In... \n", "3446 [Can the President fire the Vice President?, C... \n", "3447 [Why do regulation golf balls have dimples?, W... \n", "3448 [What are the best ways to explain evolution b... \n", "\n", "[3449 rows x 2 columns]" ], "text/html": [ "\n", "
\n", "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
conditiongroup
0Which question should I ask on Quora?[What are good questions to ask on Quora?, Why...
1What causes a nightmare?[Why do I have nightmares?, Why do we get Nigh...
2If I do not monetize YouTube videos & upload c...[Can I upload part of anime videos on YouTube ...
3Did Ben Affleck shine more than Christian Bale...[According to you, whose Batman performance wa...
4What are the effects of demonitization of 500 ...[How does demonetization of the 500 and 1000 n...
.........
3444Who invented the bra?[When and why was bra invented?, When was the ...
3445What are the ways that India and Pakistan can ...[How can there be everlasting peace between In...
3446Can the president replace the vice president w...[Can the President fire the Vice President?, C...
3447Why do golf Ball have dimple?[Why do regulation golf balls have dimples?, W...
3448What is natural selection? Why does it occur?[What are the best ways to explain evolution b...
\n", "

3449 rows × 2 columns

\n", "
\n", "
\n", "\n", "
\n", " \n", "\n", " \n", "\n", " \n", "
\n", "\n", "\n", "
\n", " \n", "\n", "\n", "\n", " \n", "
\n", "\n", "
\n", " \n", " \n", " \n", "
\n", "\n", "
\n", "
\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "result_df", "summary": "{\n \"name\": \"result_df\",\n \"rows\": 3449,\n \"fields\": [\n {\n \"column\": \"condition\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 3449,\n \"samples\": [\n \"What are the best bank exam books?\",\n \"How do I unpop a clogged ear?\",\n \"What are some common examples of renewable resources?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"group\",\n \"properties\": {\n \"dtype\": \"object\",\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 51 } ] }, { "cell_type": "code", "source": [ "! pip install datasets" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "SQbTP5gTTHsu", "outputId": "6981fbac-2f99-470a-e7a4-398cee89eb9a" }, "execution_count": 52, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting datasets\n", " Downloading datasets-3.5.0-py3-none-any.whl.metadata (19 kB)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from datasets) (3.18.0)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from datasets) (2.0.2)\n", "Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (18.1.0)\n", "Collecting dill<0.3.9,>=0.3.0 (from datasets)\n", " Downloading dill-0.3.8-py3-none-any.whl.metadata (10 kB)\n", "Requirement already satisfied: pandas in /usr/local/lib/python3.11/dist-packages (from datasets) (2.2.2)\n", "Requirement already satisfied: requests>=2.32.2 in /usr/local/lib/python3.11/dist-packages (from datasets) (2.32.3)\n", "Requirement already satisfied: tqdm>=4.66.3 in /usr/local/lib/python3.11/dist-packages (from datasets) (4.67.1)\n", "Collecting xxhash (from datasets)\n", " Downloading xxhash-3.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (12 kB)\n", "Collecting multiprocess<0.70.17 (from datasets)\n", " Downloading multiprocess-0.70.16-py311-none-any.whl.metadata (7.2 kB)\n", "Collecting fsspec<=2024.12.0,>=2023.1.0 (from fsspec[http]<=2024.12.0,>=2023.1.0->datasets)\n", " Downloading fsspec-2024.12.0-py3-none-any.whl.metadata (11 kB)\n", "Requirement already satisfied: aiohttp in /usr/local/lib/python3.11/dist-packages (from datasets) (3.11.15)\n", "Requirement already satisfied: huggingface-hub>=0.24.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (0.30.1)\n", "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from datasets) (24.2)\n", "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from datasets) (6.0.2)\n", "Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (2.6.1)\n", "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (1.3.2)\n", "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (25.3.0)\n", "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (1.5.0)\n", "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (6.3.1)\n", "Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (0.3.1)\n", "Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (1.18.3)\n", "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.24.0->datasets) (4.13.0)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (3.4.1)\n", "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (3.10)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (2.3.0)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (2025.1.31)\n", "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2.8.2)\n", "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2025.2)\n", "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2025.2)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.17.0)\n", "Downloading datasets-3.5.0-py3-none-any.whl (491 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m491.2/491.2 kB\u001b[0m \u001b[31m20.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hDownloading dill-0.3.8-py3-none-any.whl (116 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m8.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hDownloading fsspec-2024.12.0-py3-none-any.whl (183 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m183.9/183.9 kB\u001b[0m \u001b[31m13.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hDownloading multiprocess-0.70.16-py311-none-any.whl (143 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m143.5/143.5 kB\u001b[0m \u001b[31m12.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hDownloading xxhash-3.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.8/194.8 kB\u001b[0m \u001b[31m14.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hInstalling collected packages: xxhash, fsspec, dill, multiprocess, datasets\n", " Attempting uninstall: fsspec\n", " Found existing installation: fsspec 2025.3.2\n", " Uninstalling fsspec-2025.3.2:\n", " Successfully uninstalled fsspec-2025.3.2\n", "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", "torch 2.6.0+cu124 requires nvidia-cublas-cu12==12.4.5.8; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-cublas-cu12 12.5.3.2 which is incompatible.\n", "torch 2.6.0+cu124 requires nvidia-cuda-cupti-cu12==12.4.127; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-cuda-cupti-cu12 12.5.82 which is incompatible.\n", "torch 2.6.0+cu124 requires nvidia-cuda-nvrtc-cu12==12.4.127; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-cuda-nvrtc-cu12 12.5.82 which is incompatible.\n", "torch 2.6.0+cu124 requires nvidia-cuda-runtime-cu12==12.4.127; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-cuda-runtime-cu12 12.5.82 which is incompatible.\n", "torch 2.6.0+cu124 requires nvidia-cudnn-cu12==9.1.0.70; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-cudnn-cu12 9.3.0.75 which is incompatible.\n", "torch 2.6.0+cu124 requires nvidia-cufft-cu12==11.2.1.3; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-cufft-cu12 11.2.3.61 which is incompatible.\n", "torch 2.6.0+cu124 requires nvidia-curand-cu12==10.3.5.147; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-curand-cu12 10.3.6.82 which is incompatible.\n", "torch 2.6.0+cu124 requires nvidia-cusolver-cu12==11.6.1.9; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-cusolver-cu12 11.6.3.83 which is incompatible.\n", "torch 2.6.0+cu124 requires nvidia-cusparse-cu12==12.3.1.170; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-cusparse-cu12 12.5.1.3 which is incompatible.\n", "torch 2.6.0+cu124 requires nvidia-nvjitlink-cu12==12.4.127; platform_system == \"Linux\" and platform_machine == \"x86_64\", but you have nvidia-nvjitlink-cu12 12.5.82 which is incompatible.\n", "gcsfs 2025.3.2 requires fsspec==2025.3.2, but you have fsspec 2024.12.0 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed datasets-3.5.0 dill-0.3.8 fsspec-2024.12.0 multiprocess-0.70.16 xxhash-3.5.0\n" ] } ] }, { "cell_type": "code", "source": [ "from datasets import Dataset, DatasetDict\n", "from sklearn.model_selection import train_test_split\n", "from huggingface_hub import login, create_repo" ], "metadata": { "id": "ANvThSSyxt61" }, "execution_count": 53, "outputs": [] }, { "cell_type": "code", "source": [ "# 转换为Hugging Face Dataset\n", "dataset = Dataset.from_pandas(result_df)\n", "\n", "# 划分数据集\n", "# 首先划分训练集和临时集 (80% train, 20% temp)\n", "train_df, temp_df = train_test_split(result_df, test_size=0.2, random_state=42)\n", "\n", "# 然后从临时集中划分验证集和测试集 (50% dev, 50% test)\n", "dev_df, test_df = train_test_split(temp_df, test_size=0.5, random_state=42)\n", "\n", "# 转换为Dataset对象\n", "train_dataset = Dataset.from_pandas(train_df)\n", "dev_dataset = Dataset.from_pandas(dev_df)\n", "test_dataset = Dataset.from_pandas(test_df)\n", "\n", "# 创建DatasetDict\n", "dataset_dict = DatasetDict({\n", " \"train\": train_dataset,\n", " \"validation\": dev_dataset,\n", " \"test\": test_dataset\n", "})\n" ], "metadata": { "id": "bmlXZD19TRDY" }, "execution_count": 54, "outputs": [] }, { "cell_type": "code", "source": [ "from google.colab import userdata\n", "userdata.get('HF_TOKEN')\n", "\n", "login(token=userdata.get('HF_TOKEN'))\n", "\n", "# 创建数据集仓库\n", "repo_id = \"bcai001/c-sts-quora-query-as-condition-group-as-pos\" # 例如: \"johnsmith/sentiment-analysis-data\"\n", "create_repo(repo_id, repo_type=\"dataset\", exist_ok=True)\n", "\n", "# 上传数据集\n", "dataset_dict.push_to_hub(repo_id, private=True)\n", "\n", "print(f\"Dataset uploaded to: https://huggingface.co/datasets/{repo_id}\")\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 227, "referenced_widgets": [ "7ce78fce0aa14620a60fa553c97ee723", "f8ab6683e0a54815a3d046a6e58f632c", "c248c1f8fa0c4d5eac09aaa33a96ee5e", "2a16b1fe34dd4048984f8e8aa8f3c2a5", "05a5f598e0a74dfd8ad8b58c0cbde79b", "433452b427e340ccbd845b42a6e7b242", "00570ed4b9c444a2bb2462ccbc5fb288", "b3115523544648ecaed834b83cbed5d9", "1c0bc022b6a341d7aeecc2fc8381a5af", "2b60380ca15c49cbbefa69339ef3ab6a", "f37c9e5a5e8c4462b37108bd6ab839eb", "aa0db46a83e24d178cbb895aa75d64f1", "33bc7d72ed38408883ace782a06925f5", "85566cfa2ec94299892122ff510d03a3", "afffea43fb674d5a8914f0f8e4eafe54", "c339898d18fa4e26a8ee4f1c6a65f852", "6152e5539ecc4f1da06b2af7b0d089fe", "9d9ed88968554aea896a58803d4027d3", "9076d4ac0d8e421a89126b55dcd96bb1", "d9177d1445134cfa86f8073e1eb18ce0", "ffe646ebf5eb48f18459060a41476080", "d4ad33fa22974e8cb667de54fc6fdc1b", "bd2c2d08157244bda13921d6516d61ad", "f85e71053b1f49e6ba271e8205956a49", "2242388fb33d4b20a52f3182ee6438b4", "78c262c3e9af47099fc9684904a8bffb", "16c674864afc4c278c409801e8697c9e", "49e239afd0ee405e8f54f1dbf4848d56", "d5ca61aca1ea49e195bf6b65c159b813", "a77579e50bad44e89064e20b77f6d9c8", "6a409e74995244649c92dd7acbeb3f50", "1b0baac01b894dd9b4bf0b2c0a9740ed", "37999fd948e642c2af98e6020327d082", "0cff935ffb2743b6bed569a4f4f393e0", "c6d65efc78cf473b990daf11159dd4c0", "ac544844e3964f4bba14b195b69e5406", "dd4c910baed347a39b7ffc94b0ffc856", "768c17c8f789489b9952de7593d30705", "fc3e5772486c42859973f3e25ee2d828", "12a568bb8133479e9f84791660b335c3", "4734681a45f549e79e09eb9b5e4b0f9b", "c6bfefed0f1e49e4aff202c484bded0a", "76d86e530c2248b69f1e1a9306ee37d2", "fa9cd5e2cd6d4560afe96dc3df3ee595", "5995e30272f246bdb82c4c018145e6ed", "ee93dc8e5e5243af8fcd58b7f8f406ce", "52bc3f36e6e2416c8c3286cadd8f108d", "17bbdb14f1db4a329d2fd6529d19876b", "c0607941f0284eb3ba36ed2c12795d3a", "a57742af98a04da2968413cea64fd023", "4fec072ec1344f5886b5016dd614be32", "10d444226a4240c088f0e97e28c27e4a", "ba81b8435d214280ba6305dbee60c70d", "405f047617c346808b18452a1318d14b", "ad90f1ef273c4dda8cf35108a13cdf6d", "7ede365033a746ba83be95a8043ff54c", "c2f32106ce304990b6f2454da926d913", "a93706f5106045ccbd04397d450d84af", "a59b5b2541a846669119dc986df5e5f1", "f60abed2dd6541c283c1702c0ac83b2a", "392b4a60fc2e408f90d00e88465b0b47", "45ab552de57d49d3b541f1eb975306d6", "4107196d970446149cf32a8ea8a9452e", "e6b535c3023249f8b3640f33ffd2adb1", "63a2f91de2c246fea86c831c5fd03e4f", "ec8641b65d664be8999f80a8a575b01e" ] }, "id": "MH4fEd_FTo5U", "outputId": "c2924580-b349-409c-fd86-c44a143b1f43" }, "execution_count": 55, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Uploading the dataset shards: 0%| | 0/1 [00:00