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mlx-examples/llms/mlx_lm
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Anchen 82f3f31d93
chore(mlx-lm): refactor server.py to utilize generate_step from utils for consistency (#491) 
* chore(mlx-lm): refactor server.py to utilize generate_step from utils for consistency

* chore(mlx-lm): update server doc

* chore: remove unused generate func
2024-02-27 06:25:24 -08:00
..
examples Support for slerp merging models (#455) 2024-02-19 20:37:15 -08:00
models [mlx-lm] Add precompiled normalizations (#451) 2024-02-22 12:40:55 -08:00
tuner Gemma support (#474) 2024-02-21 08:47:13 -08:00
__init__.py [mlx-lm] Add precompiled normalizations (#451) 2024-02-22 12:40:55 -08:00
convert.py Lazy loading models for faster convert and merge (#462) 2024-02-20 13:36:55 -08:00
fuse.py feat(mlx-lm): add de-quant for fuse.py (#365) 2024-01-25 18:59:32 -08:00
generate.py Add top-p sampling for text generation (#486) 2024-02-26 06:18:11 -08:00
LORA.md Support for slerp merging models (#455) 2024-02-19 20:37:15 -08:00
lora.py LoRA: Extract the run function for easy use in scripts file (#482) 2024-02-26 19:35:04 -08:00
MERGE.md Support for slerp merging models (#455) 2024-02-19 20:37:15 -08:00
merge.py Lazy loading models for faster convert and merge (#462) 2024-02-20 13:36:55 -08:00
py.typed Add py.typed to support PEP-561 (type-hinting) (#389) 2024-01-30 21:17:38 -08:00
README.md feat: move lora into mlx-lm (#337) 2024-01-23 08:44:37 -08:00
requirements.txt [mlx-lm] Add precompiled normalizations (#451) 2024-02-22 12:40:55 -08:00
SERVER.md chore(mlx-lm): refactor server.py to utilize generate_step from utils for consistency (#491) 2024-02-27 06:25:24 -08:00
server.py chore(mlx-lm): refactor server.py to utilize generate_step from utils for consistency (#491) 2024-02-27 06:25:24 -08:00
UPLOAD.md Mlx llm package (#301) 2024-01-12 10:25:56 -08:00
utils.py Add top-p sampling for text generation (#486) 2024-02-26 06:18:11 -08:00

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.