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matlok/python-audio-copilot-training-using-class-knowledge-graphs-2024-01-27

Python Copilot Audio Training using Class with Knowledge Graphs This dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset. Details Each class method has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet dbytes column and the associated source code file_path identifier.… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-audio-copilot-training-using-class-knowledge-graphs-2024-01-27.

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1---2license:3- other4pretty_name: >-5  python copilot audio training using class with knowledge graphs collected on 2024-01-276dataset_info:7- config_name: v1_train_transformers_src_and_pytorch8  splits:9  - name: v1_train_transformers_src_and_pytorch10- config_name: v2_train_text_generation_inference11  splits:12  - name: v2_train_text_generation_inference13- config_name: v3_pytorch_distributed_fsdp14  splits:15  - name: v3_pytorch_distributed_fsdp16- config_name: view_schema17  splits:18  - name: view_schema19configs:20- config_name: v1_train_transformers_src_and_pytorch21  data_files:22  - split: v1_train_transformers_src_and_pytorch23    path: train/train_0001_transformers_src_and_pytorch.parquet24- config_name: v2_train_text_generation_inference25  data_files:26  - split: v2_train_text_generation_inference27    path: train/train_0002_text_generation_inference.parquet28- config_name: v3_pytorch_distributed_fsdp29  data_files:30  - split: v3_pytorch_distributed_fsdp31    path: train/train_0003_pytorch_fsdp.parquet32- config_name: view_schema33  data_files:34  - split: view_schema35    path: files/lok-python-copilot-audio.class-v1_00000717.parquet36size_categories:37- 100K<n<1M38tags:39- python-copilot40- python-coding41- python-architecture42- knowledge-graphs43- multimodal44- text-image-audio45- fine-tuning46- training47- question-answering48- image-knowledge-graph49- alpaca50- mp351- png52- text53- instruct54- class55- classes56# supported task_categories57# 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, other58task_categories:59- text-to-audio60- audio-to-audio61- question-answering62# supported task_ids63# 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-answering64task_ids:65- parsing66---67 68## Python Copilot Audio Training using Class with Knowledge Graphs69 70This 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.71 72### Details73 74Each class method has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet **dbytes** column and the associated source code **file_path** identifier.75 76- Rows: 13549677- Size: 284.6 GB78- Data type: mp379- Format: narrated alpaca question and answer pairs using two voices80 81### Schema82 83```84{85    "audio_path": "string",86    "audio_type": "string",87    "dbytes": "string",88    "dbytes_len": "int64",89    "file_path": "string",90    "file_path_len": "int64",91    "lang": "string",92    "lang_len": "int64",93    "recsize": "int64"94}95```96 97### How to use the dataset98 99```python100from datasets import load_dataset101 102ds = load_dataset("matlok/python-audio-copilot-training-using-class-knowledge-graphs-2024-01-27", data_dir="files")103```104