README.md

---
license: mit
language:
- en
base_model: inclusionAI/Ring-flash-linear-2.0
pipeline_tag: text-generation
library_name: mlx
tags:
- moe
- mlx
---

# mlx-community/Ring-flash-linear-2.0-4bit

This model [mlx-community/Ring-flash-linear-2.0-4bit](https://huggingface.co/mlx-community/Ring-flash-linear-2.0-4bit) was
converted to MLX format from [inclusionAI/Ring-flash-linear-2.0](https://huggingface.co/inclusionAI/Ring-flash-linear-2.0)
using mlx-lm version **0.28.2**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Ring-flash-linear-2.0-4bit")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
```