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Hugging Face Transformers vs Weave

A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.

Not the right match-up?
HU Hugging Face Transformers State-of-the-art machine learning model library VS WE Weave Toolkit for tracking and evaluating LLM applications
FeatureHugging Face TransformersWeave
CategorySelf-Hosted AISelf-Hosted AI
LicenseApache-2.0Apache-2.0
LanguagePythonPython
Setup difficultyHardMedium
Min. RAM8,192 MB1,024 MB
Deploymentbare-metal, sourcedocker, source
GitHub stars★ 163,456★ 1,113
First released20182023
ReplacesOpenAI APILangSmith

Why pick each one

Choose Hugging Face Transformers if…

  • Released under the Apache-2.0 license
  • Mature project with 163.5k GitHub stars
  • Written in Python
Hugging Face Transformers details

Choose Weave if…

  • Released under the Apache-2.0 license
  • First-class Docker support for quick deployment
  • Active community (1.1k GitHub stars)
  • Written in Python
Weave details

Frequently asked questions

Is Hugging Face Transformers or Weave better?

Neither is universally better. Hugging Face Transformers has the larger community, while Weave is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.

Are Hugging Face Transformers and Weave free and open-source?

Yes. Hugging Face Transformers is licensed under Apache-2.0 and Weave under Apache-2.0. Both can be self-hosted at no software cost.

Can I run Hugging Face Transformers and Weave with Docker?

Hugging Face Transformers: check the project docs for container support. Weave: yes.

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