Skip to content

AsTonyshment/metaseq

 
 

Repository files navigation

Metaseq

A codebase for working with Open Pre-trained Transformers.

Community Integrations

Using OPT with 🤗 Transformers

The OPT 125M--66B models are now available in Hugging Face Transformers. You can access them under the facebook organization on the Hugging Face Hub

Using OPT-175B with Alpa

The OPT 125M--175B models are now supported in the Alpa project, which enables serving OPT-175B with more flexible parallelisms on older generations of GPUs, such as 40GB A100, V100, T4, M60, etc.

Using OPT with Colossal-AI

The OPT models are now supported in the Colossal-AI, which helps users to efficiently and quickly deploy OPT models training and inference, reducing large AI model budgets and scaling down the labor cost of learning and deployment.

Using OPT with CTranslate2

The OPT 125M--66B models can be executed with CTranslate2, which is a fast inference engine for Transformer models. The project integrates the SmoothQuant technique to allow 8-bit quantization of OPT models. See the usage example to get started.

Using OPT with FasterTransformer

The OPT models can be served with FasterTransformer, a highly optimized inference framework written and maintained by NVIDIA. We provide instructions to convert OPT checkpoints into FasterTransformer format and a usage example with some benchmark results.

Getting Started in Metaseq

Follow setup instructions here to get started.

Documentation on workflows

Background Info

Support

If you have any questions, bug reports, or feature requests regarding either the codebase or the models released in the projects section, please don't hesitate to post on our Github Issues page.

Please remember to follow our Code of Conduct.

Contributing

We welcome PRs from the community!

You can find information about contributing to metaseq in our Contributing document.

The Team

Metaseq is currently maintained by the CODEOWNERS: Susan Zhang, Naman Goyal, Punit Singh Koura, Moya Chen, Kurt Shuster, Ruan Silva, David Esiobu, Igor Molybog, Peter Albert, Sharan Narang, Andrew Poulton, Nikolay Bashlykov, Binh Tang, and Uriel Singer.

Previous maintainers include: Stephen Roller, Anjali Sridhar, Christopher Dewan.

License

The majority of metaseq is licensed under the MIT license, however portions of the project are available under separate license terms:

About

Repo for external large-scale work

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 96.0%
  • Scala 2.2%
  • Other 1.8%