zephyr-7b-beta-4bit

Zephyr 7B β (✨ 4-bit)

Zephyr is a series of language models that are trained to act as helpful assistants. Zephyr-7B-β is the second model in the series, and is a fine-tuned version of mistralai/Mistral-7B-v0.1 that was trained on on a mix of publicly available, synthetic datasets using Direct Preference Optimization (DPO). We found that removing the in-built alignment of these datasets boosted performance on MT Bench and made the model more helpful. However, this means that model is likely to generate problematic text when prompted to do so. You can find more details in the technical report.

This repository contains the zephyr-7b-beta weights in npz format in 4-bit suitable for use with Apple's MLX framework (from 0.6.0 onwards).

Use with MLX

pip install mlx
pip install huggingface_hub hf_transfer
git clone https://github.com/ml-explore/mlx-examples.git
cd mlx-examples

# Download model
export HF_HUB_ENABLE_HF_TRANSFER=1
huggingface-cli download --local-dir-use-symlinks False --local-dir zephyr-7b-beta-4bit mlx-community/zephyr-7b-beta-4bit

# Run example
python llms/mistral/mistral.py --model-path zephyr-7b-beta-4bit --prompt "My name is"

Please, refer to the original model card for more details on Zephyr 7B β.

Prompt Format

Please note that this model expects a specific prompt structure. Here is an example:

<|system|>
You are a pirate chatbot who always responds with Arr!</s>
<|user|>
There's a llama on my lawn, how can I get rid of him?</s>
<|assistant|>