---
license: mit
language:
- en
base_model: inclusionAI/Ring-mini-sparse-2.0-exp
pipeline_tag: text-generation
library_name: transformers
tags:
- moe
- mlx
- mlx-my-repo
---

# TomLucidor/Ring-mini-sparse-2.0-exp-mlx-8Bit

The Model [TomLucidor/Ring-mini-sparse-2.0-exp-mlx-8Bit](https://huggingface.co/TomLucidor/Ring-mini-sparse-2.0-exp-mlx-8Bit) was converted to MLX format from [inclusionAI/Ring-mini-sparse-2.0-exp](https://huggingface.co/inclusionAI/Ring-mini-sparse-2.0-exp) using mlx-lm version **0.29.1**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("TomLucidor/Ring-mini-sparse-2.0-exp-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)
```