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hugging-science

Discover scientific datasets and models on Hugging Face.

Updated May 8, 2026
Search Tags:#machine learning#genomics#AI/ML#Hugging Face#scientific datasets
One-click install
npx skills add https://github.com/Zeyuyang-0420/bio-ai-research-skills --skill hugging-science-zeyuyang-0420
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hugging-science
Source: https://github.com/Zeyuyang-0420/bio-ai-research-skills/tree/main/categories/ml-training-ai/hugging-science
Command: npx skills add https://github.com/Zeyuyang-0420/bio-ai-research-skills --skill hugging-science-zeyuyang-0420

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires transformers, huggingface_hub, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of discovering and utilizing the vast array of scientific datasets, models, and resources available on Hugging Face, specifically designed for AI/ML applications in scientific domains.

Core Features & Use Cases

  • Scientific Dataset Discovery: Access a curated catalog of scientific datasets, models, and blog posts.
  • Model Usage: Run models via transformers or the Hugging Face Inference API.
  • Interactive Spaces: Call Spaces like BoltzGen for interactive demos.
  • Use Case: If you are working on a genomics project and need a dataset or model for sequence analysis, this Skill can guide you to the right resource.

Quick Start

To find a dataset for genomics, use the 'hugging-science' skill and provide the keyword 'genomics'.

Frequently Asked Questions about hugging-science

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find scientific datasets and models for machine learning on Hugging Face?▼

To find scientific datasets and models for machine learning, you can query a curated catalog of Hugging Face resources by providing domain keywords like genomics. This indexes scientific datasets, models, and blog posts for AI/ML research.

Can I run models directly using the Hugging Face Inference API with this setup?▼

Yes, you can run models directly using the Hugging Face Inference API or the transformers library. This setup enables model execution and allows you to call interactive Spaces like BoltzGen for interactive demos.

Do I need a specific Python environment to access Hugging Face scientific resources?▼

Yes, accessing Hugging Face scientific resources requires a Python environment with transformers and huggingface_hub installed. You also need Hugging Face API access configured to retrieve datasets and run models.

What is the best way to discover AI/ML resources for genomics sequence analysis?▼

The best way to discover AI/ML resources for genomics sequence analysis is to search a curated scientific index using the keyword 'genomics'. This guides you to relevant datasets and models specifically for sequence analysis projects.

Are there limitations when using transformers for scientific dataset retrieval?▼

Limitations when using transformers for scientific dataset retrieval include requiring valid Hugging Face API access and a properly configured Python environment. Without these dependencies, model execution and dataset retrieval will not function correctly.

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