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MODEL Listed

Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

For developers building multimodal applications, Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive offers a specialized approach to vision-language tasks. Based on the Qwen architecture, this 35B parameter model is fine-tuned for high-fidelity image-to-text reasoning and complex instruction following. Unlike standard restricted models, this version is optimized for unfiltered responses, making it a practical choice for researchers and developers working on edge cases, creative writing, or datasets where safety alignment might otherwise suppress nuanced or raw information. It excels in visual reasoning, OCR, and descriptive captioning. Integration is straightforward via Hugging Face, supporting standard multimodal pipelines. While the 'Aggressive' tuning increases response volatility, it provides a significant advantage for developers needing high-entropy outputs that aren't constrained by heavy-handed RLHF filters, allowing for more direct and precise alignment with complex user prompts.

HauhauCSimage text to text
01 / MODEL CARD

Model card

For developers building multimodal applications, Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive offers a specialized approach to vision-language tasks. Based on the Qwen architecture, this 35B parameter model is fine-tuned for high-fidelity image-to-text reasoning and complex instruction following. Unlike standard restricted models, this version is optimized for unfiltered responses, making it a practical choice for researchers and developers working on edge cases, creative writing, or datasets where safety alignment might otherwise suppress nuanced or raw information. It excels in visual reasoning, OCR, and descriptive captioning. Integration is straightforward via Hugging Face, supporting standard multimodal pipelines. While the 'Aggressive' tuning increases response volatility, it provides a significant advantage for developers needing high-entropy outputs that aren't constrained by heavy-handed RLHF filters, allowing for more direct and precise alignment with complex user prompts.

Model typeimage text to text
ProviderHauhauCS
Licenseapache-2.0
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
View model source
Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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