Congrats on implementing your model! Now it's time to test it out.
Congrats on implementing your model! Now it's time to test it out.
To make your model usable via the command line interface to `lm-eval` using `main.py`, you'll need to tell `lm-eval` what your model's name is.
To make your model usable via the command line interface to `lm-eval` using `main.py`, you'll need to tell `lm-eval` what your model's name is.
This is done via a *decorator*, `lm_eval.api.registry.register_model`. Using `register_model()`, one can both tell the package what the model's name(s) to be used are when invoking it with `python main.py --model <name>` and alert `lm-eval` to the model's existence.
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## Conclusion
After reading this guide, you should be able to add new model APIs or implementations to the Eval Harness library!
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After reading this guide, you should be able to add new model APIs or implementations to the Eval Harness library!
