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Datasets
All datasets matching “docs”transformers.js-docspolicy-docs
Public Policy at Hugging Face
AI Policy at Hugging Face is a multidisciplinary and cross-organizational workstream. Instead of being part of a vertical communications or global affairs organization, our policy work is rooted in the expertise of our many researchers and developers, from Ethics and Society Regulars and legal team to machine learning engineers working on healthcare, art, and evaluations.
What we work on is informed by our Hugging Face community needs and experiences… See the full description on the dataset page: https://huggingface.co/datasets/huggingface/policy-docs.docs-imagesdiffusers-images-docsdolma3-6t-sample-100000-docs
dolma3-6t-sample-100000-docs
Materialized stratified sample of 100,000 docs per bin (~58k source-shard files, ~186 GB) from the deduplicated 6T Dolma3 corpus. Seed 42, materialized by 128 Modal workers (worker_0000/ through worker_0127/).
Layout
HCAI-Lab/dolma3-6t-sample-100000-docs/
├── bin_summary.csv
├── sample_contract.json
└── worker_NNNN/
└── soc127__phase1_pool_shared__...__shard_NNNNNNNN.jsonl.zst (~450 files per worker)
Dual-access… See the full description on the dataset page: https://huggingface.co/datasets/HCAI-Lab-GT/dolma3-6t-sample-100000-docs.pixmo-docs
PixMo-Docs
We now recommend using CoSyn-400k and CoSyn-point over these
datasets. They are improved versions with more images categories and an improved generation pipeline.
PixMo-Docs is a collection of synthetic question-answer pairs about various kinds of computer-generated images, including charts, tables, diagrams, and documents.
The data was created by using the Claude large language model to generate code that can be executed to render an image,
and using GPT-4o mini to… See the full description on the dataset page: https://huggingface.co/datasets/allenai/pixmo-docs.