---
license: agpl-3.0
language:
- en
library_name: transformers
tags:
- qwen
- qwen3
- qwen3.6
- moe
- distillation
- chain-of-thought
- agentic
- claude-fable-5
- claude-opus-4.7
- tool-use
- chained-distill
- qwable
- qwable-v2
- mlx
- mlx-my-repo
pipeline_tag: text-generation
base_model: lordx64/Qwable-v2
datasets:
- lordx64/fable-sft-combined-v2
- lordx64/agentic-distill-fable-5-sft
- lordx64/fable-tool-use-sft
---

# keXjos/Qwable-v2-mlx-4Bit

The Model [keXjos/Qwable-v2-mlx-4Bit](https://huggingface.co/keXjos/Qwable-v2-mlx-4Bit) was converted to MLX format from [lordx64/Qwable-v2](https://huggingface.co/lordx64/Qwable-v2) using mlx-lm version **0.31.2**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("keXjos/Qwable-v2-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)
```