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ResearchHugging Face

Hugging Face

Models, datasets, papers, spaces. The AI research commons.

Categories
ResearchInfra
Pricing
FREEMIUM
Hosting
Cloud
Platforms
WebAPICLI
Models
Model-agnostic
Verified
Jul 5, 2026

Source-of-truth for open-weights models and datasets. Daily-paper feed for tracking research; Spaces for trying ideas without setting up infra. The default home for any model not behind a paid API.

Capabilities 4

What it actually does — grouped by capability family.

  • Multi-model access (primary capability)
  • Model inference / serving (primary capability)
  • GPU compute (secondary capability)
  • Fine-tuning / training (secondary capability)

Pros & cons

  • Largest open model + dataset hub
  • Runnable Spaces demos, no infra
  • Daily papers + community
  • Transformers/Diffusers libraries anchor it
  • Hosting/inference quality varies by repo
  • Serious inference needs paid Endpoints/GPUs
  • Discovery noisy at this scale

Tags

View all Research
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    • model-hosting
    • fine-tuning
    • api
    • open-source
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    • prototyping
    • gemini
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    Ollama

    Ollama

    Run open-weight LLMs locally with one command. OpenAI-compatible API.

    The de-facto way to pull and run open-weight models (Llama, Qwen, Gemma, DeepSeek, gpt-oss) on your own machine — no API key, no data leaving the device. Ships native macOS/Windows/Linux apps, an OpenAI-compatible server, and official Python/JS libraries. MIT-licensed and free locally; an optional paid Ollama Cloud runs larger models.

    One-command pull-and-run
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    • local
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  • View Modal details
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    Modal Labs

    Serverless GPUs. Run training, inference, batch jobs from Python.

    Define cloud workloads in Python, deploy with one command — GPU access on demand, fast cold starts, fair-share pricing. The default 'I need to fine-tune a model from a Jupyter cell' platform.

    Python-decorator infra, no YAML/Dockerfiles
    SDK lock-in; migrating means rewriting
    • gpu
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    • python
    • training