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Awni Hannun
2025-03-13 13:23:04 -07:00
parent 61e64358a8
commit 37691af2b1
8 changed files with 290 additions and 28 deletions
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.circleci/config.yml
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version: 2.1
orbs:
apple: ml-explore/pr-approval@0.1.0
jobs:
linux_build_and_test:
docker:
- image: cimg/python:3.9
steps:
- checkout
- run:
name: Run style checks
command: |
pip install pre-commit
pre-commit run --all
if ! git diff --quiet; then echo 'Style checks failed, please install pre-commit and run pre-commit run --all and push the change'; exit 1; fi
mlx_lm_build_and_test:
macos:
xcode: "15.2.0"
resource_class: macos.m1.large.gen1
steps:
- checkout
- run:
name: Install dependencies
command: |
brew install python@3.9
python3.9 -m venv env
source env/bin/activate
pip install --upgrade pip
pip install unittest-xml-reporting
cd llms/
pip install -e ".[test]"
- run:
name: Run Python tests
command: |
source env/bin/activate
python -m xmlrunner discover -v llms/tests -o test-results/
- store_test_results:
path: test-results
workflows:
build_and_test:
when:
matches:
pattern: "^(?!pull/)[-\\w]+$"
value: << pipeline.git.branch >>
jobs:
- mlx_lm_build_and_test
- linux_build_and_test
prb:
when:
matches:
pattern: "^pull/\\d+(/head)?$"
value: << pipeline.git.branch >>
jobs:
- hold:
type: approval
- apple/authenticate:
context: pr-approval
- mlx_lm_build_and_test:
requires: [ hold ]
- linux_build_and_test:
requires: [ hold ]
.gitignore
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# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Vim
*.swp
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
pip-wheel-metadata/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
.python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
# PEP 582; used by e.g. github.com/David-OConnor/pyflow
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# IDE files
.idea/
.vscode/
# .DS_Store files
.DS_Store
.pre-commit-config.yaml
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repos:
- repo: https://github.com/psf/black-pre-commit-mirror
rev: 25.1.0
hooks:
- id: black
- repo: https://github.com/pycqa/isort
rev: 6.0.0
hooks:
- id: isort
args:
- --profile=black
ACKNOWLEDGMENTS.md
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@@ -5,13 +5,8 @@ with a short description of your contribution(s) below. For example:
- Jane Smith: Added the `foo` example.
MLX Examples was developed with contributions from the following individuals:
MLX LM was developed with contributions from the following individuals:
- Juarez Bochi: Added support for T5 models.
- Sarthak Yadav: Added the `cifar` and `speechcommands` examples.
- Shunta Saito: Added support for PLaMo models.
- Gabrijel Boduljak: Implemented `CLIP`.
- Markus Enzweiler: Added the `cvae` examples.
- Prince Canuma: Helped add support for `Starcoder2` models.
- Shiyu Li: Added the `Segment Anything Model`.
- Gökdeniz Gülmez: Added support for `MiniCPM`, `Helium`, `Mamba version 1`, `OLMoE` archtectures and support for `full-fine-tuning`.
CONTRIBUTING.md
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@@ -1,11 +1,54 @@
# Contributing to MLX LM
We want to make contributing to this project as easy and transparent as
possible.
## Pull Requests
1. Fork and submit pull requests to the repo.
2. If you've added code that should be tested, add tests.
3. Every PR should have passing tests and at least one review.
4. For code formatting install `pre-commit` using something like `pip install pre-commit` and run `pre-commit install`.
This should install hooks for running `black` and `clang-format` to ensure
consistent style for C++ and python code.
You can also run the formatters manually as follows on individual files:
```bash
clang-format -i file.cpp
```
```bash
black file.py
```
or,
```bash
# single file
pre-commit run --files file1.py
# specific files
pre-commit run --files file1.py file2.py
```
or run `pre-commit run --all-files` to check all files in the repo.
## Issues
We use GitHub issues to track public bugs. Please ensure your description is
clear and has sufficient instructions to be able to reproduce the issue.
## License
By contributing to mlx-lm, you agree that your contributions will be licensed
under the LICENSE file in the root directory of this source tree.
## Adding New Models
Below are some tips to port LLMs available on Hugging Face to MLX.
Before starting checkout the [general contribution
guidelines](https://github.com/ml-explore/mlx-examples/blob/main/CONTRIBUTING.md).
Next, from this directory, do an editable install:
From this directory, do an editable install:
```shell
pip install -e .
@@ -17,7 +60,7 @@ Then check if the model has weights in the
convert it.
After that, add the model file to the
[`mlx_lm/models`](https://github.com/ml-explore/mlx-examples/tree/main/llms/mlx_lm/models)
[`mlx_lm/models`](https://github.com/ml-explore/mlx-lm/tree/main/mlx_lm/models)
directory. You can see other examples there. We recommend starting from a model
that is similar to the model you are porting.
@@ -35,12 +78,12 @@ To determine the model layer names, we suggest either:
in the Hugging Face repo.
To add LoRA support edit
[`mlx_lm/tuner/utils.py`](https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/tuner/utils.py#L27-L60)
[`mlx_lm/tuner/utils.py`](https://github.com/ml-explore/mlx-lm/blob/main/mlx_lm/tuner/utils.py#L27-L60)
Finally, add a test for the new modle type to the [model
tests](https://github.com/ml-explore/mlx-examples/blob/main/llms/tests/test_models.py).
tests](https://github.com/ml-explore/mlx-lm/blob/main/tests/test_models.py).
From the `llms/` directory, you can run the tests with:
You can run the tests with:
```shell
python -m unittest discover tests/
README.md
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## Generate Text with LLMs and MLX
## MLX LM
MLX LM is a Python package for generating text and fine-tuning large language
models on Apple silicon with MLX.
Some key features include:
* Integration with the Hugging Face Hub to easily use thousands of LLMs with a
single command.
* Support for quantizing and uploading models to the Hugging Face Hub.
* [Low-rank and full model
fine-tuning](https://github.com/ml-explore/mlx-lm/blob/main/mlx_lm/LORA.md)
with support for quantized models.
* Distributed inference and fine-tuning with `mx.distributed`
The easiest way to get started is to install the `mlx-lm` package:
@@ -14,18 +27,12 @@ pip install mlx-lm
conda install -c conda-forge mlx-lm
```
The `mlx-lm` package also has:
- [LoRA, QLoRA, and full fine-tuning](https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/LORA.md)
- [Merging models](https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/MERGE.md)
- [HTTP model serving](https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/SERVER.md)
### Quick Start
To generate text with an LLM use:
```bash
mlx_lm.generate --prompt "Hi!"
mlx_lm.generate --prompt "How tall is Mt Everest?"
```
To chat with an LLM use:
@@ -71,7 +78,7 @@ To see a description of all the arguments you can do:
```
Check out the [generation
example](https://github.com/ml-explore/mlx-examples/tree/main/llms/mlx_lm/examples/generate_response.py)
example](https://github.com/ml-explore/mlx-lm/tree/main/mlx_lm/examples/generate_response.py)
to see how to use the API in more detail.
The `mlx-lm` package also comes with functionality to quantize and optionally
@@ -216,14 +223,14 @@ not be supplied explicitly.
Prompt caching can also be used in the Python API in order to to avoid
recomputing the prompt. This is useful in multi-turn dialogues or across
requests that use the same context. See the
[example](https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/examples/chat.py)
[example](https://github.com/ml-explore/mlx-lm/blob/main/mlx_lm/examples/chat.py)
for more usage details.
### Supported Models
`mlx-lm` supports thousands of Hugging Face format LLMs. If the model you want to
run is not supported, file an
[issue](https://github.com/ml-explore/mlx-examples/issues/new) or better yet,
[issue](https://github.com/ml-explore/mlx-lm/issues/new) or better yet,
submit a pull request.
Here are a few examples of Hugging Face models that work with this example:
mlx_lm/utils.py
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@@ -118,7 +118,7 @@ def wired_limit(model: nn.Module, streams: Optional[List[mx.Stream]] = None):
f"[WARNING] Generating with a model that requires {model_mb} MB "
f"which is close to the maximum recommended size of {max_rec_mb} "
"MB. This can be slow. See the documentation for possible work-arounds: "
"https://github.com/ml-explore/mlx-examples/tree/main/llms#large-models"
"https://github.com/ml-explore/mlx-lm/tree/main/llms#large-models"
)
old_limit = mx.metal.set_wired_limit(max_rec_size)
try:
setup.py
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@@ -21,7 +21,7 @@ setup(
readme="README.md",
author_email="mlx@group.apple.com",
author="MLX Contributors",
url="https://github.com/ml-explore/mlx-examples",
url="https://github.com/ml-explore/mlx-lm",
license="MIT",
install_requires=requirements,
packages=["mlx_lm", "mlx_lm.models", "mlx_lm.tuner"],