---
license: apache-2.0
base_model: DavidAU/Qwen3-ST-The-Next-Generation-II-E32-v1-256k-ctx-6B
datasets:
- progs2002/star-trek-tng-scripts
language:
- en
pipeline_tag: text-generation
tags:
- programming
- code generation
- code
- coding
- coder
- chat
- brainstorm
- qwen
- qwen3
- qwencoder
- brainstorm 20x
- creative
- all uses cases
- Jan-V1
- float32
- horror
- science fiction
- fantasy
- Star Trek
- finetune
- thinking
- reasoning
- mlx
library_name: mlx
---

# Qwen3-ST-The-Next-Generation-II-E32-v1-256k-ctx-6B-qx86-hi-mlx

This model [Qwen3-ST-The-Next-Generation-II-E32-v1-256k-ctx-6B-qx86-hi-mlx](https://huggingface.co/Qwen3-ST-The-Next-Generation-II-E32-v1-256k-ctx-6B-qx86-hi-mlx) was
converted to MLX format from [DavidAU/Qwen3-ST-The-Next-Generation-II-E32-v1-256k-ctx-6B](https://huggingface.co/DavidAU/Qwen3-ST-The-Next-Generation-II-E32-v1-256k-ctx-6B)
using mlx-lm version **0.27.1**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("Qwen3-ST-The-Next-Generation-II-E32-v1-256k-ctx-6B-qx86-hi-mlx")

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)
```