metadata
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 for more details on the model.
Use with mlx
pip install mlx-lm
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
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