You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
all issues/todos related to the environment will be listed here as a sub-issue
Minimum Submission Requirements
Use OpenEnv (latest release). Build on top of the framework; don’t reinvent the wheel.
A working training script using Unsloth or Hugging Face TRL, ideally as a Colab notebook so judges can re-run it.
Evidence that you actually trained; at minimum, loss and reward plots from a real run.
A short writeup: a mini-blog on Hugging Face or a < 2 minute video on YouTube explaining what your environment does and what you trained, or a short slide deck of presentation. Please make sure that all materials are linked from your README file so that judges can access them easily.
Push your environment to a Hugging Face Space so it’s discoverable and runnable.
A README that motivates the problem, explains how the env works, and shows results.
README should have a link to the environment in the Hugging Face Space. It should also have all additional references to other materials (e.g. videos, blog posts, slides, presentations, etc.) that you want to include.
Please do not include big video files in your Env submission on HF Hub as we would like to have a small size for each env (Please use url as reference link to additional materials).
all issues/todos related to the environment will be listed here as a sub-issue
Minimum Submission Requirements
README should have a link to the environment in the Hugging Face Space. It should also have all additional references to other materials (e.g. videos, blog posts, slides, presentations, etc.) that you want to include.
Please do not include big video files in your Env submission on HF Hub as we would like to have a small size for each env (Please use url as reference link to additional materials).