mlx-examples

mirror of https://github.com/ml-explore/mlx-examples.git synced 2025-09-23 23:28:12 +08:00

Files

Awni Hannun 8801beb66f Add olmo2 (#1128 )

* add olmo2

* add olmo2

2024-12-02 11:42:58 -08:00

examples

Generation refactor: part 2 (#1099 )

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models

Add olmo2 (#1128 )

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tuner

Add olmo2 (#1128 )

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__init__.py

Fix detokenizer space match for quote (#1072 )

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_version.py

Put prompt processing in same stream (#1122 )

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cache_prompt.py

[MLX LM] Sampler refactor + a few improvements (#1094 )

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chat.py

Generation refactor: part 2 (#1099 )

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convert.py

override dtype with quant (#1062 )

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fuse.py

Adding full finetuning (#903 )

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generate.py

Generation refactor: part 2 (#1099 )

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gguf.py

Fix export to gguf (#993 )

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LORA.md

LoRA: update tools datasets docs (#1063 )

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lora.py

LoRA: Support HuggingFace dataset via data parameter (#996 )

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MANAGE.md

Add model management functionality for local caches (#736 )

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manage.py

Add model management functionality for local caches (#736 )

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MERGE.md

Create executables for generate, lora, server, merge, convert (#682 )

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merge.py

Create executables for generate, lora, server, merge, convert (#682 )

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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

Wire models in MLX LM (#1069 )

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sample_utils.py

Generation refactor: part 2 (#1099 )

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SERVER.md

Fix object property value in mlx_lm.server chat completions response to match OpenAI spec (#1119 )

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server.py

Fix object property value in mlx_lm.server chat completions response to match OpenAI spec (#1119 )

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tokenizer_utils.py

Generation refactor: part 2 (#1099 )

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UPLOAD.md

Mlx llm package (#301 )

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utils.py

Accept mx.array type for prompt argument for stream_generate (#1125 )

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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.