Instructions to use mlx-community/Nous-Hermes-2-Mixtral-8x7B-DPO-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Nous-Hermes-2-Mixtral-8x7B-DPO-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Nous-Hermes-2-Mixtral-8x7B-DPO-4bit mlx-community/Nous-Hermes-2-Mixtral-8x7B-DPO-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
| language: | |
| - en | |
| license: apache-2.0 | |
| tags: | |
| - Mixtral | |
| - instruct | |
| - finetune | |
| - chatml | |
| - DPO | |
| - RLHF | |
| - gpt4 | |
| - synthetic data | |
| - distillation | |
| - mlx | |
| base_model: mistralai/Mixtral-8x7B-v0.1 | |
| model-index: | |
| - name: Nous-Hermes-2-Mixtral-8x7B-DPO | |
| results: [] | |
| # mlx-community/Nous-Hermes-2-Mixtral-8x7B-DPO-4bit | |
| This model was converted to MLX format from [`NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO`](). | |
| Refer to the [original model card](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO) for more details on the model. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("mlx-community/Nous-Hermes-2-Mixtral-8x7B-DPO-4bit") | |
| response = generate(model, tokenizer, prompt="hello", verbose=True) | |
| ``` | |
| ## Use with mlx_lm cli | |
| ```bash | |
| pip install -U mlx-lm | |
| python3 -m mlx_lm.generate --model mlx-community/Nous-Hermes-2-Mixtral-8x7B-DPO-4bit --prompt "<|im_start|>system\nYou are an accurate, educational, and helpful information assistant<|im_end|>\n<|im_start|>user\nWhat is the difference between awq vs gptq quantitization?<|im_end|>\n<|im_start|>assistant\n" --max-tokens 2048 | |
| ``` |