license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3.6-27B/blob/main/LICENSE
language:
- en
- zh
- ru
- es
- fr
- it
- ja
- ko
- af
- de
- ar
- tr
- is
- pl
- sw
- sv
- nl
- he
- id
- uk
- fa
- pa
- pt
- ms
- fi
- el
base_model: TheCluster/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking-MLX-mixed-9.4bit
library_name: mlx
tags: - heretic
- abliterated
- uncensored
- decensored
- 9bit
- mixed-precision
- 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
- all use cases
- mlx
- mlx-my-repo
pipeline_tag: image-text-to-text
culturerevolt/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking-MLX-mixed-9.4bit-mlx-4Bit
The Model culturerevolt/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking-MLX-mixed-9.4bit-mlx-4Bit was converted to MLX format from TheCluster/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking-MLX-mixed-9.4bit using mlx-lm version 0.31.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("culturerevolt/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking-MLX-mixed-9.4bit-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)