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null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "7b4ead13a6e34a038268f5848f7a7b54": { "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": "markdown", "source": [ "## Using ColQwen2 with transformers\n", "\n", "ColQwen2, state-of-the-art visual document retrieval model is now in transformers!\n", "\n", "Here's a notebook to show how to do similarity/retrieval with it. Let's install transformers from main for now." ], "metadata": { "id": "LDVowlaaK5P7" } }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "VAmN3_LvKjNL", "outputId": "0facabbe-65e4-45ba-9150-381b9ad7b777" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.0/6.0 MB\u001b[0m \u001b[31m71.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m3.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K 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torch\n", "\n", "model_name = \"vidore/colqwen2-v1.0-hf\"\n", "\n", "model = ColQwen2ForRetrieval.from_pretrained(\n", " model_name,\n", " torch_dtype=torch.bfloat16,\n", " device_map=\"auto\",\n", " attn_implementation=\"flash_attention_2\",\n", ")\n", "processor = ColQwen2Processor.from_pretrained(model_name)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 484, "referenced_widgets": [ "b6fc374b26ba4d73bf8c39da9bfded80", "78cb27265325446b8ad40fdd533e818d", "3ededd5b7d7b470a9d9f19da99f60cb6", "7e25413502ac49248d794bd77510b8d0", "2b13ef42cf724ad584b35e6aedb75729", "0a8e81e803884e6a9c917db4a95f0d94", "0f7d3acbc0ca4969b6ed9c998ec4bdbb", "e2fc14c60a034c389ebe5394d2becdaf", "9362167da12f467e90744658f32537a1", "2a70f2d14c5c4fa38b7de264c16fb828", "fb07c774d70c41798a02468f07afbb52", "79bcedf04e134bc98795a8363051cd3b", "24f4fc633512495fbfbdc49de29b471c", "45fbd74c03d5498e826af3ea7b92ce4c", "48b3c66c530247aaa385658bbc726261", "558fa5025d07461e95ca7d679d299141", 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the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", "You will be able to reuse this secret in all of your notebooks.\n", "Please note that authentication is recommended but still optional to access public models or datasets.\n", " warnings.warn(\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "config.json: 0%| | 0.00/6.08k [00:00] 157.34K --.-KB/s in 0.05s \n", "\n", "2025-06-02 15:18:24 (2.99 MB/s) - ‘US-original-Declaration-1776.jpg’ saved [161116/161116]\n", "\n", "--2025-06-02 15:18:24-- https://upload.wikimedia.org/wikipedia/commons/thumb/4/4c/Romeoandjuliet1597.jpg/500px-Romeoandjuliet1597.jpg\n", "Resolving upload.wikimedia.org (upload.wikimedia.org)... 198.35.26.112, 2620:0:863:ed1a::2:b\n", "Connecting to upload.wikimedia.org (upload.wikimedia.org)|198.35.26.112|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 98494 (96K) [image/jpeg]\n", "Saving to: ‘500px-Romeoandjuliet1597.jpg’\n", "\n", "500px-Romeoandjulie 100%[===================>] 96.19K --.-KB/s in 0.04s \n", "\n", "2025-06-02 15:18:24 (2.25 MB/s) - ‘500px-Romeoandjuliet1597.jpg’ saved [98494/98494]\n", "\n" ] } ] }, { "cell_type": "markdown", "source": [ "Preprocess our inputs." ], "metadata": { "id": "przbTn71OXSx" } }, { "cell_type": "code", "source": [ "from PIL import Image\n", "\n", "from transformers.utils.import_utils import is_flash_attn_2_available\n", "\n", "\n", "images = [\n", " Image.open(\"/content/500px-Romeoandjuliet1597.jpg\"),\n", " Image.open(\"/content/US-original-Declaration-1776.jpg\"),\n", "]\n", "\n", "queries = [\n", " \"When was the United States Declaration of Independence proclaimed?\",\n", " \"Who printed the edition of Romeo and Juliet?\",\n", "]\n", "\n", "# Process the inputs\n", "inputs_images = processor(images=images).to(model.device)\n", "inputs_text = processor(text=queries).to(model.device)" ], "metadata": { "id": "nW9QC3_TKmkx" }, "execution_count": 8, "outputs": [] }, { "cell_type": "markdown", "source": [ "We can now infer." ], "metadata": { "id": "yXJurtigObn9" } }, { "cell_type": "code", "source": [ "# Forward pass\n", "with torch.no_grad():\n", " image_embeddings = model(**inputs_images).embeddings\n", " query_embeddings = model(**inputs_text).embeddings\n", "\n", "# Score the queries against the images\n", "scores = processor.score_retrieval(query_embeddings, image_embeddings)\n", "\n", "print(\"Retrieval scores (query x image):\")\n", "print(scores)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "FKr8bS7VNQT5", "outputId": "81592aad-7354-4e6d-f7e1-f7819b7f977a" }, "execution_count": 9, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Retrieval scores (query x image):\n", "tensor([[ 8.6250, 16.5000],\n", " [16.3750, 9.3750]], dtype=torch.bfloat16)\n" ] } ] }, { "cell_type": "markdown", "source": [ "As you can see, the first image is most similar to second text prompt and the second image is the most similar to first prompt!" ], "metadata": { "id": "lh1W6607Oexk" } }, { "cell_type": "markdown", "source": [ "To learn more, check out [the model repository](https://huggingface.co/vidore/colqwen2-v1.0) and the [transformers docs](https://huggingface.co/docs/transformers/main/en/model_doc/colqwen2)." ], "metadata": { "id": "t2yXdAWzOn_h" } } ] }