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---
license: apache-2.0
base_model: cognitivecomputations/Dolphin-Mistral-24B-Venice-Edition
tags:
- mlx
---
# synergy-float/Dolphin-Mistral-24B-Venice-Edition-mlx-4Bit
The Model [synergy-float/Dolphin-Mistral-24B-Venice-Edition-mlx-4Bit](https://huggingface.co/synergy-float/Dolphin-Mistral-24B-Venice-Edition-mlx-4Bit) was converted to MLX format from [cognitivecomputations/Dolphin-Mistral-24B-Venice-Edition](https://huggingface.co/cognitivecomputations/Dolphin-Mistral-24B-Venice-Edition) using mlx-lm version **0.22.3**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("synergy-float/Dolphin-Mistral-24B-Venice-Edition-mlx-4Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
```