---
base_model: Danau5tin/Orca-Agent-v0.1
license: apache-2.0
datasets:
- Danau5tin/terminal-tasks
tags:
- agent
- code
- multi-agent
- mlx
- mlx-my-repo
---

# ncls-p/Orca-Agent-v0.1-mlx-8Bit

The Model [ncls-p/Orca-Agent-v0.1-mlx-8Bit](https://huggingface.co/ncls-p/Orca-Agent-v0.1-mlx-8Bit) was converted to MLX format from [Danau5tin/Orca-Agent-v0.1](https://huggingface.co/Danau5tin/Orca-Agent-v0.1) using mlx-lm version **0.26.4**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("ncls-p/Orca-Agent-v0.1-mlx-8Bit")

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)
```