Hugging Face's Top Datasets: Fueling AI Innovation
Hugging Face recently unveiled its most popular datasets, each playing a crucial role in advancing artificial intelligence. These datasets cater to a wide range of AI applications, from instruction following to complex multimodal understanding. Below, we explore these datasets, ranked by download count.
Table of Contents
- FineWeb-Edu (HuggingFaceFW)
- TxT360 (LLM360)
- FineWeb 2 (HuggingFaceFW)
- Common Corpus (PleIAs)
- Cosmopedia (HuggingFaceTB)
- HelpSteer2 (Nvidia)
- Orca-AgentInstruct-1M-v1 (Microsoft)
- SmolTalkDataset (HuggingFaceTB)
- FinePersonas (Argilla)
- FineVideo (HuggingFaceFV)
- Infinity Instruct (BAAI)
- PersonaHub (proj-persona)
- Two-Million-Bluesky-Posts (Alpin Dale)
- xlam-function-calling-60k (Salesforce)
- OpenO1-SFT (O1-OPEN)
- MMMLU (OpenAI)
- FRAMES (Google)
- Reasoning-Base-20k (KingNish)
- arXiver (Neuralwork)
- 5CD-AILLaVA-CoT-o1-Instruct (5CD-AI)
- Related Articles
- Summary
Dataset Highlights:
Each dataset entry below provides key features, use cases, and a standout feature. Links to the Hugging Face page for each dataset are omitted for brevity but are readily available through a simple online search.
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FineWeb-Edu (HuggingFaceFW): (Likes: 573, Downloads: 318,907) High-quality educational web content, filtered for middle-school to grade-school level understanding. Highlight: Curated for advanced academic and training models.
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TxT360 (LLM360): (Likes: 217, Downloads: 102,124) A massive 15T token corpus, created using advanced deduplication techniques. Highlight: Scalable pipeline for high-quality data.
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FineWeb 2 (HuggingFaceFW): (Likes: 363, Downloads: 88,657) Multilingual dataset supporting over 1000 languages and scripts. Highlight: Promotes global NLP inclusivity.
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Common Corpus (PleIAs): (Likes: 196, Downloads: 24,844) Over 2 trillion tokens from diverse sources, emphasizing ethical standards. Highlight: Benchmark resource for robust AI model development.
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Cosmopedia (HuggingFaceTB): (Likes: 570, Downloads: 20,840) A synthetic dataset of 30 million samples generated by Mixtral-8x7B-Instruct-v0.1. Highlight: Pioneering scalable synthetic data generation.
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HelpSteer2 (Nvidia): (Likes: 390, Downloads: 13,799) 21,000 samples with annotations focusing on helpfulness and correctness. Highlight: Top scores on major benchmarks.
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Orca-AgentInstruct-1M-v1 (Microsoft): (Likes: 404, Downloads: 12,877) 1 million synthetic instruction pairs covering various tasks. Highlight: Improved reasoning and factual correctness.
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SmolTalkDataset (HuggingFaceTB): (Likes: 260, Downloads: 11,523) Synthetic dataset for supervised fine-tuning. Highlight: Enhanced task-specific performance.
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FinePersonas (Argilla): (Likes: 363, Downloads: 6,853) 21 million detailed personas for diverse synthetic text generation. Highlight: Facilitates rich, context-specific synthetic outputs.
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FineVideo (HuggingFaceFV): (Likes: 283, Downloads: 5,434) Dataset focused on video understanding. Highlight: Powers cutting-edge multimodal video analysis.
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Infinity Instruct (BAAI): (Likes: 574, Downloads: 5,284) Large-scale instruction dataset for reasoning and coding. Highlight: Advances open-source AI capabilities.
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PersonaHub (proj-persona): (Likes: 475, Downloads: 3,846) 1 billion personas for synthetic data synthesis. Highlight: Facilitates diverse character interactions.
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Two-Million-Bluesky-Posts (Alpin Dale): (Likes: 193, Downloads: 3,155) 2 million public posts from Bluesky Social. Highlight: Explores linguistic trends.
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xlam-function-calling-60k (Salesforce): (Likes: 395, Downloads: 2,567) Focused on function-calling applications. Highlight: High accuracy on function-calling benchmarks.
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OpenO1-SFT (O1-OPEN): (Likes: 271, Downloads: 2,171) Supports Supervised Fine-Tuning for Chain-of-Thought reasoning. Highlight: Improved reasoning self-consistency.
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MMMLU (OpenAI): (Likes: 438, Downloads: 1,761) Covers 57 topics in 14 languages. Highlight: High standard for multilingual comprehension.
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FRAMES (Google): (Likes: 176, Downloads: 1,757) RAG evaluation dataset with multi-hop questions. Highlight: Tests multi-step retrieval.
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Reasoning-Base-20k (KingNish): (Likes: 194, Downloads: 1,581) Includes step-by-step reasoning explanations. Highlight: Improves reasoning accuracy.
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arXiver (Neuralwork): (Likes: 355, Downloads: 790) 63,357 arXiv papers in multi-markdown format. Highlight: Streamlines technical content integration.
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5CD-AILLaVA-CoT-o1-Instruct (5CD-AI): (Likes: 64, Downloads: 598) Enables Chain-of-Thought reasoning in vision-language models. Highlight: Integrates structured outputs for complex tasks.
Related Articles: (Links omitted for brevity)
- 400 Categorized Large Language Model (LLM) Datasets
- 25 Open Datasets for Deep Learning
- 28 Websites to Find Datasets
- 10 Datasets by INDIAai
- 10 Open Source Datasets for LLM Training
Summary:
This selection of leading datasets showcases the dynamic landscape of AI development. Their diverse applications and contributions highlight the ongoing progress in creating more robust, versatile, and ethically sound AI systems.
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