
# 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
```
{"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 mixtral Mixtral instruct finetune chatml DPO RLHF gpt4 synthetic data distillation en base_model:mistralai/Mixtral-8x7B-v0.1 license:apache-2.0 region:us