Today we’re releasing the weights for Laguna M.1,
our most capable model to date, with a 256K context length.
Both base and post-trained checkpoints are now available on Hugging Face under Apache 2.0.
when maintaining a python monorepo, having ruff + pyrefly + ast-grep is such a blessing
i am so happy when the organization works in a sensible subset of the language
and when there is business logic that ends up being bad™️ ... ban it with ast-grep
agents, rejoice
Laguna M.1 and XS.2 now support 256K context.
Laguna M.1 is now live with a 256K context window on the Poolside API and OpenRouter.
With this update, it reaches 45.8% on Terminal-Bench 2.0, improving long-horizon performance.
Laguna XS.2 is also moving to 256K today, with the updated config already available on Hugging Face.
Both models remain free to use.
Over 1T tokens have been processed since launch 4 weeks ago. Excited to see what people build with the longer context window.
Today we’re publishing the technical report behind Laguna M.1 and Laguna XS.2.
This report opens up more of what went into them: Model Factory, pre-training data, distributed training, post-training, agent RL, quantization, and evaluation.
https://t.co/RWk2F9IrAI
Today we’re publishing the technical report behind Laguna M.1 and Laguna XS.2.
This report opens up more of what went into them: Model Factory, pre-training data, distributed training, post-training, agent RL, quantization, and evaluation.
https://t.co/RWk2F9IrAI
@gabriberton This will soon be handled at the type checker level. With pyrefly, you can enforce these as static type checks rather than enforcing it only at runtime through assert or jaxtyping
https://t.co/ZhJLVPMwck
Just published my notes from this year's Python Typing Summit at PyCon US. If you've ever been curious what one of these is like from the inside: intersection types, constraint sets in ty, tensor shapes in Pyrefly, Guido on direction. 🐍📝 https://t.co/AbGxwrbTlp #PyConUS