OpenLLM encourages contributions by welcoming users to incorporate their custom Large Language Models (LLMs) into the ecosystem. You can set up your development environment by referring to our Developer Guide.
All the relevant code for incorporating a new model resides within
$GIT_ROOT/openllm-core/src/openllm_core/config
model_name
in snake_case.
Here's your roadmap:
- Generate model configuration file:
$GIT_ROOT/openllm-core/src/openllm_core/config/configuration_{model_name}.py
- Update
$GIT_ROOT/openllm-core/src/openllm_core/config/__init__.py
to import the new model - Add your new model entry in
$GIT_ROOT/openllm-core/src/openllm_core/config/configuration_auto.py
with a tuple of themodel_name
alongside with theModelConfig
- Run
bash all.sh
Note
$GIT_ROOT
refers to $(git rev-parse --show-toplevel)
For a working example, check out any existing model.
File Name: configuration_{model_name}.py
This file is dedicated to specifying docstrings, default prompt templates, default parameters, as well as additional fields for the models.
After establishing the model config and implementation class, register them in
the __init__
file, and the tuple under CONFIG_MAPPING_NAMES
in openllm-core/src/openllm_core/config/configuration_auto.py#CONFIG_MAPPING_NAMES. Basically you need to register ModelConfig
classes with its given name for for_model
to use.
Once you have completed the checklist above, raise a PR and the OpenLLMs maintainer will review it ASAP. Once the PR is merged, you should be able to see your model in the next release! 🎉 🎊