mlx-examples

mirror of https://github.com/ml-explore/mlx-examples.git synced 2025-09-24 07:38:09 +08:00

Files

Anchen fbed720d6f chore(mlx-lm): fix the top_p implementation. (#602 )

* chore(mlx-lm): clean up the top p imp

* chore: clean up

* chore: add test

* chore: address comments

* chore: clean up docs string

* chore: clean up test

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examples

Add dropout parameter to lora configuration (#599 )

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models

Make attention faster for a some models (#574 )

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tuner

Add dropout parameter to lora configuration (#599 )

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__init__.py

Fix import warning (#479 )

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convert.py

add dequantize option to mlx_lm/convert.py (#547 )

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fuse.py

feat(mlx-lm): export the GGUF (fp16) format model weights from fuse.py (#555 )

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generate.py

chore(mlx-lm): enable to apply default chat template (#577 )

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gguf.py

feat(mlx-lm): export the GGUF (fp16) format model weights from fuse.py (#555 )

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LORA.md

feat(mlx-lm): export the GGUF (fp16) format model weights from fuse.py (#555 )

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lora.py

Add dropout parameter to lora configuration (#599 )

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MERGE.md

Support for slerp merging models (#455 )

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merge.py

feat: add update_config functionality (#531 )

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py.typed

Add py.typed to support PEP-561 (type-hinting) (#389 )

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README.md

feat: move lora into mlx-lm (#337 )

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requirements.txt

Support for OpenAI’s fine-tuning dataset format (#548 )

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sample_utils.py

chore(mlx-lm): fix the top_p implementation. (#602 )

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SERVER.md

Prevent llms/mlx_lm from serving the local directory as a webserver (#498 )

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server.py

Set finish_reason in response (#592 )

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UPLOAD.md

Mlx llm package (#301 )

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utils.py

chore(mlx-lm): fix the top_p implementation. (#602 )

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version.py

feat(mlx-lm): export the GGUF (fp16) format model weights from fuse.py (#555 )

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README.md

Generate Text with MLX and 🤗 Hugging Face

This an example of large language model text generation that can pull models from the Hugging Face Hub.

For more information on this example, see the README in the parent directory.

This package also supports fine tuning with LoRA or QLoRA. For more information see the LoRA documentation.