Model Details
Full Model IDHauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
Pipeline / Taskimage-text-to-text
Library—
Downloads (all-time)3.5M
Likes2.2K
Last Modified4/17/2026
Author / OrgHauhauCS
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-text-to-text", model="HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
ggufuncensoredqwen3.6moevisionmultimodalimage-text-to-textenzhmultilingualbase_model:Qwen/Qwen3.6-35B-A3Bbase_model:quantized:Qwen/Qwen3.6-35B-A3Blicense:apache-2.0endpoints_compatibleregion:usimatrixconversational
More image-text-to-text Models
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: image-text-to-text
This model is designed for the image-text-to-text task. Explore more models for this use case.
All image-text-to-text Models →📊 Popularity
⬇ Downloads3.5M
❤️ Community Likes2.2K
🛠️ Requirements
- →Check docs for installation steps.
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.