---
pipeline_tag: text-generation
inference: false
tags:
- notus
- mlx
language:
- en
license: mit
library_name: mlx
---

# Notus 7B v1

<div align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/60f0608166e5701b80ed3f02/dj-spsk9eXMMXVGxK6jRz.png" alt="A banner representing Notus, the wind god of the south, in a mythical and artistic style. The banner features a strong, swirling breeze, embodying the warm, wet character of the southern wind. Gracefully flowing across the scene are several paper planes, caught in the gentle yet powerful gusts of Notus. The background is a blend of warm colors, symbolizing the heat of the south, with hints of blue and green to represent the moisture carried by this wind. The overall atmosphere is one of dynamic movement and warmth."/>
</div>

Notus is a collection of fine-tuned models using Direct Preference Optimization (DPO) and related RLHF techniques following a data-first approach. This model is the first version, fine-tuned with DPO on top of [`alignment-handbook/zephyr-7b-sft-full`](https://huggingface.co./alignment-handbook/zephyr-7b-sft-full), which is the SFT model produced to create [`HuggingFaceH4/zephyr-7b-beta`](https://huggingface.co./HuggingFaceH4/zephyr-7b-beta). 

More information at [argilla/notus-7b-v1](https://huggingface.co./argilla/notus-7b-v1)

This repository contains the `notus-7b-v1` weights in `npz` format suitable for use with Apple's MLX framework.

## Use with MLX

```bash
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 notus-7b-v1 alvarobartt/notus-7b-v1

# Run example
python llms/mistral/mistral.py --model-path notus-7b-v1 --prompt "My name is"
```

Please, refer to the [original model card](https://huggingface.co./argilla/notus-7b-v1) for more details on Notus 7B v1.

## Prompt Format

Please note that this model expects a specific prompt structure.

```
<|system|>
{system_prompt}</s>
<|user|>
{user_prompt}</s>
<|assistant|>
```

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|>
```