library_name: transformers
license: mit
base_model:
- Mia-AiLab/Qwable-3.6-27b
tags: - multimodal
- vision-language
- audio
- agent
- video-understanding
- long-context
- abliterated
- uncensored
- GGUF
- MTP
huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF
This is an uncensored version of Mia-AiLab/Qwable-3.6-27b created with abliteration.
This ablation was performed entirely using llama.cpp's GGUF model, without relying on Transformers,
For the specific ablation method, please refer to cvector-generator.
GGUF
Please use the latest version of ggml-org/llama.cpp
The version we tested is ggml-org/llama.cpp-b9190
apt-get update
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y
git clone https://github.com/ggml-org/llama.cpp
cmake llama.cpp -B llama.cpp/build \
-DBUILD_SHARED_LIBS=OFF -DGGML_CUDA=ON
cmake --build llama.cpp/build --config Release -j --clean-first --target llama-cli llama-mtmd-cli llama-server llama-gguf-split
cp llama.cpp/build/bin/llama-* llama.cpp
./llama.cpp/llama-cli \
-m huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF/Huihui-Qwen3.6-27B-abliterated-ggml-model-Q4_K.gguf \
-ngl 99 -c 262144 -fa on -np 1 \
--spec-type draft-mtp --spec-draft-n-max 6
Files
| File | Size | out (ffn_down/ssm_out/attn_output) |
Everything else |
|---|---|---|---|
Huihui-Qwable-3.6-27b-abliterated-Q4_K_M_Q8.gguf |
19.1 GiB | (ffn_down/ssm_out/attn_output) (Q8_0) |
(ffn_gate/ssm_out/ffn_up) (Q4_K), (attn_v/attn_qkv) (Q6_K), MTP(blk.64.) |
Huihui-Qwable-3.6-27b-abliterated-Q4_K_M_F16.gguf |
25.8 GiB | (ffn_down/ssm_out/attn_output) (F16) |
(ffn_gate/ssm_out/ffn_up) (Q4_K), (attn_v/attn_qkv) (Q6_K), MTP(blk.64.) |
Huihui-Qwable-3.6-27b-abliterated-F16.gguf |
50.9 GiB | (ffn_down/ssm_out/attn_output) (F16) |
(ffn_gate/ssm_out/ffn_up) (F16) , (attn_v/attn_qkv) (F16), MTP(blk.64.) |
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 bears no responsibility for any consequences arising from its use.
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