andyjack/Huihui-Qwen3.6-35B-A3B-abliterated-GGUF overview
huihui ai/Huihui Qwen3.6 35B A3B abliterated This is an uncensored version of Qwen/Qwen3.6 35B A3B https://huggingface.co/Qwen/Qwen3.6 35B A3B created with abl…
Runs locally from ~861.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | andyjack/Huihui-Qwen3.6-35B-A3B-abliterated-GGUF |
|---|---|
| Author | andyjack |
| Pipeline | image-text-to-text |
| License | apache-2.0 |
| Base model | Qwen/Qwen3.6-35B-A3B |
| Last modified | 2026-07-06T18:38:06.000Z |
Model README
---
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3.6-35B-A3B/blob/main/LICENSE
pipeline_tag: image-text-to-text
base_model:
- Qwen/Qwen3.6-35B-A3B
tags:
- abliterated
- uncensored
---
huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated
This is an uncensored version of Qwen/Qwen3.6-35B-A3B created with abliteration (see remove-refusals-with-transformers to know more about it).
This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
I made GGUF's in Q8 for almost perfect full quality and MXFP4 to fit on a single RTX 3090 or 4090.
You can also export GGML_CUDA_ENABLE_UNIFIED_MEMORY=1 to enable unified memory on linux with Nvidia.
Both model quants tested with mmproj-BF16.gguf for multi-modal image use.
llama.cpp latest version
llama.cpp/build/bin/llama-server \
-m Qwen3.6-35b-abliterated-Q8_0.gguf \
--mmproj mmproj-BF16.gguf \
--host 0.0.0.0 \
--port 11434 \
--api-key XXX \
--flash-attn on \
--cache-type-k q8_0 \
--cache-type-v q8_0\
--n-gpu-layers 99 \
--split-mode layer \
--no-mmap \
--temp 0.6 \
--top-p 0.95 \
--top-k 20 \
--repeat-penalty 1.0 \
--repeat-last-n = 256 \
--jinja \
-c 262144 \
-b 2048 \
-ub 2048 \
--parallel 1
Usage Warnings
- Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs.
- Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security.
- Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences.
- Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications.
- Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content.
- No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai nor I bear any responsibility for any consequences arising from its use.
Donation
Your donation helps us continue our further development and improvement, a cup of coffee can do it.
- bitcoin:
bc1q6nvh39fcmy0de0ezepnn2z0rn4dme9yjal77ahRun andyjack/Huihui-Qwen3.6-35B-A3B-abliterated-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models