mirror of
https://github.com/ml-explore/mlx-examples.git
synced 2025-06-24 01:17:28 +08:00
parent
2fce02acd8
commit
d9e1d9c0ef
@ -17,30 +17,6 @@ jobs:
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pre-commit run --all
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pre-commit run --all
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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
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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
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mlx_lm_build_and_test:
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macos:
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xcode: "15.2.0"
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resource_class: macos.m1.large.gen1
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steps:
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- checkout
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- run:
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name: Install dependencies
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command: |
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brew install python@3.9
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python3.9 -m venv env
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source env/bin/activate
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pip install --upgrade pip
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pip install unittest-xml-reporting
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cd llms/
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pip install -e ".[test]"
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- run:
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name: Run Python tests
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command: |
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source env/bin/activate
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python -m xmlrunner discover -v llms/tests -o test-results/
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- store_test_results:
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path: test-results
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workflows:
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workflows:
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build_and_test:
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build_and_test:
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when:
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when:
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@ -48,7 +24,6 @@ workflows:
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pattern: "^(?!pull/)[-\\w]+$"
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pattern: "^(?!pull/)[-\\w]+$"
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value: << pipeline.git.branch >>
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value: << pipeline.git.branch >>
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jobs:
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jobs:
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- mlx_lm_build_and_test
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- linux_build_and_test
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- linux_build_and_test
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prb:
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prb:
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@ -4,12 +4,12 @@ This repo contains a variety of standalone examples using the [MLX
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framework](https://github.com/ml-explore/mlx).
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framework](https://github.com/ml-explore/mlx).
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The [MNIST](mnist) example is a good starting point to learn how to use MLX.
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The [MNIST](mnist) example is a good starting point to learn how to use MLX.
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Some more useful examples are listed below. Check-out [MLX
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Some more useful examples are listed below.
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LM](https://github.com/ml-explore/mlx-lm) for a more fully featured Python
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package for LLMs with MLX.
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### Text Models
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### Text Models
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- [MLX LM](llms/README.md) a package for LLM text generation, fine-tuning, and more.
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- [Transformer language model](transformer_lm) training.
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- [Transformer language model](transformer_lm) training.
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- Minimal examples of large scale text generation with [LLaMA](llms/llama),
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- Minimal examples of large scale text generation with [LLaMA](llms/llama),
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[Mistral](llms/mistral), and more in the [LLMs](llms) directory.
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[Mistral](llms/mistral), and more in the [LLMs](llms) directory.
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@ -30,6 +30,7 @@ Some more useful examples are listed below.
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- Speech recognition with [OpenAI's Whisper](whisper).
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- Speech recognition with [OpenAI's Whisper](whisper).
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- Audio compression and generation with [Meta's EnCodec](encodec).
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- Audio compression and generation with [Meta's EnCodec](encodec).
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- Music generation with [Meta's MusicGen](musicgen).
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### Multimodal models
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### Multimodal models
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@ -1,3 +1,9 @@
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# DEPRECATED
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The mlx-lm package has moved to a [new repo](https://github.com/ml-explore/mlx-lm).
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The package here will be removed soon. Send new contributions and issues to the MLX LM repo.
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## Generate Text with LLMs and MLX
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## Generate Text with LLMs and MLX
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The easiest way to get started is to install the `mlx-lm` package:
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The easiest way to get started is to install the `mlx-lm` package:
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@ -1,3 +1,9 @@
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# DEPRECATED
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The mlx-lm package has moved to a [new repo](https://github.com/ml-explore/mlx-lm).
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The package here will be removed soon. Send new contributions and issues to the MLX LM repo.
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## Generate Text with MLX and :hugs: Hugging Face
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## Generate Text with MLX and :hugs: Hugging Face
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This an example of large language model text generation that can pull models from
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This an example of large language model text generation that can pull models from
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