MLX
Safetensors
mixtral
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README.md CHANGED
@@ -6,38 +6,30 @@ language:
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  - es
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  - en
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  license: apache-2.0
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- library_name: mlx
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  tags:
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- - moe
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- inference: false
 
 
 
 
 
 
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  ---
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- # Model Card for Mixtral-8x7B
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- The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mixtral-8x7B outperforms Llama 2 70B on most benchmarks we tested.
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- For full details of this model please read our [release blog post](https://mistral.ai/news/mixtral-of-experts/).
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- ## Instruction format
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- This format must be strictly respected, otherwise the model will generate sub-optimal outputs.
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-
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- The template used to build a prompt for the Instruct model is defined as follows:
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- ```
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- <s> [INST] Instruction [/INST] Model answer</s> [INST] Follow-up instruction [/INST]
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- ```
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- Note that `<s>` and `</s>` are special tokens for beginning of string (BOS) and end of string (EOS) while [INST] and [/INST] are regular strings.
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-
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- ## Run the model
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  ```bash
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- # Install mlx, mlx-examples, huggingface-cli
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- pip install mlx
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- pip install huggingface_hub hf_transfer
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- git clone https://github.com/ml-explore/mlx-examples.git
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- # Download model
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- export HF_HUB_ENABLE_HF_TRANSFER=1
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- huggingface-cli download --local-dir Mixtral-8x7B-Instruct-v0.1 mlx-community/Mixtral-8x7B-Instruct-v0.1
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- # Run example
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- python mlx-examples/mixtral/mixtral.py --model_path Mixtral-8x7B-Instruct-v0.1
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- ```
 
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  - es
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  - en
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  license: apache-2.0
 
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  tags:
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+ - mlx
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+ inference:
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+ parameters:
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+ temperature: 0.5
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+ widget:
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+ - messages:
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+ - role: user
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+ content: What is your favorite condiment?
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  ---
 
 
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+ # mlx-community/Mixtral-8x7B-Instruct-v0.1
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+ The Model [mlx-community/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mlx-community/Mixtral-8x7B-Instruct-v0.1) was converted to MLX format from [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) using mlx-lm version **0.12.0**.
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+ ## Use with mlx
 
 
 
 
 
 
 
 
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  ```bash
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+ pip install mlx-lm
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+ ```
 
 
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+ ```python
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+ from mlx_lm import load, generate
 
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+ model, tokenizer = load("mlx-community/Mixtral-8x7B-Instruct-v0.1")
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+ response = generate(model, tokenizer, prompt="hello", verbose=True)
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+ ```
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+ "architectures": [
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+ "transformers_version": "4.36.0.dev0",
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+ "vocab_size": 32000
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+ }
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