---
language:
- en
- zh
license: apache-2.0
tags:
- fine tune
- creative
- creative writing
- fiction writing
- plot generation
- sub-plot generation
- story generation
- scene continue
- storytelling
- fiction story
- science fiction
- romance
- all genres
- story
- writing
- vivid prosing
- vivid writing
- fiction
- roleplaying
- bfloat16
- all use cases
- unsloth
- heretic
- uncensored
- abliterated
- mlx
- mlx-my-repo
library_name: transformers
pipeline_tag: image-text-to-text
base_model: DavidAU/Qwen3.5-9B-Claude-4.6-OS-HERETIC-UNCENSORED-INSTRUCT
---

# enet45/Qwen3.5-9B-Claude-4.6-OS-HERETIC-UNCENSORED-INSTRUCT-mlx-8Bit

The Model [enet45/Qwen3.5-9B-Claude-4.6-OS-HERETIC-UNCENSORED-INSTRUCT-mlx-8Bit](https://huggingface.co/enet45/Qwen3.5-9B-Claude-4.6-OS-HERETIC-UNCENSORED-INSTRUCT-mlx-8Bit) was converted to MLX format from [DavidAU/Qwen3.5-9B-Claude-4.6-OS-HERETIC-UNCENSORED-INSTRUCT](https://huggingface.co/DavidAU/Qwen3.5-9B-Claude-4.6-OS-HERETIC-UNCENSORED-INSTRUCT) 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("enet45/Qwen3.5-9B-Claude-4.6-OS-HERETIC-UNCENSORED-INSTRUCT-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)
```