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Qwen3.5-27B-Claude-4.6-OS-Auto-Variable-Heretic-Uncensored-Thinking-mlx-2Bit
enet45/Qwen3.5-27B-Claude-4.6-OS-Auto-Variable-Heretic-Uncensored-Thinking-mlx-2Bit
Qwen3.5-27B-Claude-4.6-OS-Auto-Variable-Heretic-Uncensored-Thinking-mlx-2Bit is a image-text-to-text model from enet45. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
The Model enet45/Qwen3.5-27B-Claude-4.6-OS-Auto-Variable-Heretic-Uncensored-Thinking-mlx-2Bit was converted to MLX format from DavidAU/Qwen3.5-27B-Claude-4.6-OS-Auto-Variable-Heretic-Uncensored-Thinking using mlx-lm v…
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From the Hugging Face model README
enet45/Qwen3.5-27B-Claude-4.6-OS-Auto-Variable-Heretic-Uncensored-Thinking-mlx-2Bit
The Model enet45/Qwen3.5-27B-Claude-4.6-OS-Auto-Variable-Heretic-Uncensored-Thinking-mlx-2Bit was converted to MLX format from DavidAU/Qwen3.5-27B-Claude-4.6-OS-Auto-Variable-Heretic-Uncensored-Thinking using mlx-lm version 0.31.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("enet45/Qwen3.5-27B-Claude-4.6-OS-Auto-Variable-Heretic-Uncensored-Thinking-mlx-2Bit")
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)
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- qwen3_5
- License
- apache-2.0
- Languages
- en, zh
- Created
- Apr 22, 2026
- Updated
- Apr 22, 2026