Awni Hannun
91 lines
2.7 KiB
Markdown
91 lines
2.7 KiB
Markdown
# Contributing to MLX LM
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We want to make contributing to this project as easy and transparent as
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possible.
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## Pull Requests
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1. Fork and submit pull requests to the repo.
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2. If you've added code that should be tested, add tests.
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3. Every PR should have passing tests and at least one review.
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4. For code formatting install `pre-commit` using something like `pip install pre-commit` and run `pre-commit install`.
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This should install hooks for running `black` and `clang-format` to ensure
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consistent style for C++ and python code.
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You can also run the formatters manually as follows on individual files:
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```bash
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clang-format -i file.cpp
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```
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```bash
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black file.py
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```
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or,
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```bash
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# single file
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pre-commit run --files file1.py
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# specific files
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pre-commit run --files file1.py file2.py
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```
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or run `pre-commit run --all-files` to check all files in the repo.
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## Issues
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We use GitHub issues to track public bugs. Please ensure your description is
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clear and has sufficient instructions to be able to reproduce the issue.
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## License
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By contributing to mlx-lm, you agree that your contributions will be licensed
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under the LICENSE file in the root directory of this source tree.
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## Adding New Models
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Below are some tips to port LLMs available on Hugging Face to MLX.
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From this directory, do an editable install:
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```shell
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pip install -e .
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```
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Then check if the model has weights in the
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[safetensors](https://huggingface.co/docs/safetensors/index) format. If not
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[follow instructions](https://huggingface.co/spaces/safetensors/convert) to
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convert it.
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After that, add the model file to the
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[`mlx_lm/models`](https://github.com/ml-explore/mlx-lm/tree/main/mlx_lm/models)
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directory. You can see other examples there. We recommend starting from a model
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that is similar to the model you are porting.
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Make sure the name of the new model file is the same as the `model_type` in the
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`config.json`, for example
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[starcoder2](https://huggingface.co/bigcode/starcoder2-7b/blob/main/config.json#L17).
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To determine the model layer names, we suggest either:
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- Refer to the Transformers implementation if you are familiar with the
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codebase.
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- Load the model weights and check the weight names which will tell you about
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the model structure.
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- Look at the names of the weights by inspecting `model.safetensors.index.json`
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in the Hugging Face repo.
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To add LoRA support edit
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[`mlx_lm/tuner/utils.py`](https://github.com/ml-explore/mlx-lm/blob/main/mlx_lm/tuner/utils.py#L27-L60)
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Finally, add a test for the new modle type to the [model
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tests](https://github.com/ml-explore/mlx-lm/blob/main/tests/test_models.py).
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You can run the tests with:
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```shell
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python -m unittest discover tests/
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```
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