Instructions to use mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-8bit --local-dir SFR-Iterative-DPO-LLaMA-3-8B-R-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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license: cc-by-nc-nd-3.0
tags:
- mlx
---
# mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-8bit
The Model [mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-8bit](https://huggingface.co/mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-8bit) was converted to MLX format from [Salesforce/SFR-Iterative-DPO-LLaMA-3-8B-R](https://huggingface.co/Salesforce/SFR-Iterative-DPO-LLaMA-3-8B-R) using mlx-lm version **0.13.0**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-8bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```
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