Image-Text-to-Text
Safetensors
English
Chinese
qwen3_5
unsloth
qwen
qwen3.5
reasoning
chain-of-thought
Dense
conversational
compressed-tensors
Instructions to use cpatonn/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-AWQ-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use cpatonn/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-AWQ-4bit with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for cpatonn/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-AWQ-4bit to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for cpatonn/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-AWQ-4bit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for cpatonn/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-AWQ-4bit to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="cpatonn/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-AWQ-4bit", max_seq_length=2048, )
- Xet hash:
- 5a3f24d1baff528abf6c1da82032fdaf2351ae7b72b8401be376bb53d244fc77
- Size of remote file:
- 5.35 GB
- SHA256:
- 9870fc0defbb50a3995f74cf1413536dbc6eb9315b0bfbdad7c94741e87ccf0d
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