--- license: - other pretty_name: >- python copilot large coding dataset dataset_info: - config_name: view_schema splits: - name: view_schema configs: - config_name: view_schema data_files: - split: view_schema path: files/lok-python-code-large-v1_00000013.parquet size_categories: - 100K<n<1M - 1M<n<10M tags: - python-copilot - python-coding - fine-tuning - training - alpaca - text - coding # supported task_categories # text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, conversational, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, other task_categories: - text-generation # supported task_ids # acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-generation, dialogue-modeling, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering task_ids: - parsing --- ## Python Copilot Large Coding Dataset This dataset is a subset of the matlok python copilot datasets. Please refer to the [Multimodal Python Copilot Training Overview](https://huggingface.co/datasets/matlok/multimodal-python-copilot-training-overview) for more details on how to use this dataset. ### Details Each row contains python code, either a class method or a global function, imported modules, base classes (if any), exceptions (ordered based off the code), returns (ordered based off the code), arguments (ordered based off the code), and more. - Rows: 2350782 - Size: 3.1 GB - Data type: text - Format: Extracted code using python AST ### Schema ```json { "args": "string", "class_bases": "string", "class_docstr": "string", "class_docstr_tok": "string", "class_name": "string", "code": "string", "code_tok": "string", "docstr": "string", "docstr_tok": "string", "file_path": "string", "filename": "string", "imports": "string", "is_member": "bool", "label_desc": "string", "label_desc_len": "int64", "label_id": "string", "lend": "int64", "lstart": "int64", "name": "string", "num_all_bases": "float64", "num_bases": "float64", "num_classes": "float64", "num_functions": "int64", "num_imports": "int64", "num_methods": "float64", "raises": "string", "returns": "string", "total_objects": "int64" } ``` ### How to use the dataset ```python from datasets import load_dataset ds = load_dataset("matlok/python-copilot-training-from-many-repos-large", data_dir="files") ```