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add MiniMax-M2 in supported models (#575)
* add MiniMax-M2 in supported models * update --------- Co-authored-by: Awni Hannun <[email protected]>
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README.md

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@@ -236,45 +236,19 @@ for more usage details.
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### Supported Models
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`mlx-lm` supports thousands of Hugging Face format LLMs. If the model you want to
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run is not supported, file an
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[issue](https://github.com/ml-explore/mlx-lm/issues/new) or better yet,
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submit a pull request.
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Here are a few examples of Hugging Face models that work with this example:
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- [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
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- [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf)
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- [deepseek-ai/deepseek-coder-6.7b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct)
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- [01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat)
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- [microsoft/phi-2](https://huggingface.co/microsoft/phi-2)
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- [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
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- [Qwen/Qwen-7B](https://huggingface.co/Qwen/Qwen-7B)
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- [pfnet/plamo-13b](https://huggingface.co/pfnet/plamo-13b)
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- [pfnet/plamo-13b-instruct](https://huggingface.co/pfnet/plamo-13b-instruct)
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- [stabilityai/stablelm-2-zephyr-1_6b](https://huggingface.co/stabilityai/stablelm-2-zephyr-1_6b)
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- [internlm/internlm2-7b](https://huggingface.co/internlm/internlm2-7b)
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- [tiiuae/falcon-mamba-7b-instruct](https://huggingface.co/tiiuae/falcon-mamba-7b-instruct)
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Most
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[Mistral](https://huggingface.co/models?library=transformers,safetensors&other=mistral&sort=trending),
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[Llama](https://huggingface.co/models?library=transformers,safetensors&other=llama&sort=trending),
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[Phi-2](https://huggingface.co/models?library=transformers,safetensors&other=phi&sort=trending),
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and
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[Mixtral](https://huggingface.co/models?library=transformers,safetensors&other=mixtral&sort=trending)
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style models should work out of the box.
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For some models (such as `Qwen` and `plamo`) the tokenizer requires you to
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enable the `trust_remote_code` option. You can do this by passing
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`--trust-remote-code` in the command line. If you don't specify the flag
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explicitly, you will be prompted to trust remote code in the terminal when
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running the model.
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For `Qwen` models you must also specify the `eos_token`. You can do this by
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passing `--eos-token "<|endoftext|>"` in the command
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line.
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These options can also be set in the Python API. For example:
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`mlx-lm` supports thousands of LLMs available on the Hugging Face Hub. If the
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model you want to run is not supported, file an
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[issue](https://github.com/ml-explore/mlx-lm/issues/new) or better yet, submit
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a pull request. Many supported models are available in various quantization
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formats in the [MLX Community](https://huggingface.co/mlx-community) Hugging
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Face organization.
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For some models the tokenizer may require you to enable the `trust_remote_code`
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option. You can do this by passing `--trust-remote-code` in the command line.
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If you don't specify the flag explicitly, you will be prompted to trust remote
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code in the terminal when running the model.
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Tokenizer options can also be set in the Python API. For example:
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```python
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model, tokenizer = load(

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