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by Huihui.ai huihui-ai/Huihui-gemma-4-12B-it-qat-q4_0-unquantized-abliterated-GGUF
This is an uncensored version of google/gemma-4-12B-it-qat-q40-unquantized created with abliteration (see remove-refusals-with-transformers to know more about it).
By Huihui.ai, published under apache-2.0, revision 2c26f29ecd20.
This is an uncensored version of google/gemma-4-12B-it-qat-q40-unquantized 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. Note: For this model, both the thinking mode and the non-thinking mode have been completely abliterated. Only layers 23-36 have been abliterated. Please use the latest version of ollama You can use huihuiai/gemma-4-abliterated:12b-qat directly, Please use the latest version of ggml-org/llama.cpp - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially…
This is an uncensored version of google/gemma-4-12B-it-qat-q4_0-unquantized 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.
Note: For this model, both the thinking mode and the non-thinking mode have been completely abliterated. Only layers 23-36 have been abliterated.
Please use the latest version of ollama
You can use huihui_ai/gemma-4-abliterated:12b-qat directly,
ollama run huihui_ai/gemma-4-abliterated:12b-qat
Please use the latest version of ggml-org/llama.cpp
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-gemma-4-12B-it-qat-q4_0-unquantized-abliterated-GGUF/Huihui-gemma-4-12B-it-qat-q4_0-unquantized-abliterated-Q4_K.gguf \
-ngl 99 -c 262144 \
--spec-type draft-mtp \
--spec-draft-n-max 4 \
--spec-draft-model huihui-ai/Huihui-gemma-4-12B-it-qat-q4_0-unquantized-abliterated-GGUF/mtp-ggml-model-bf16.gguf
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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6 files, 32.3 GB in total. The weights are 4 files totalling 32.3 GB in gguf.
| File | Type | Size | SHA-256 |
|---|---|---|---|
| Huihui-gemma-4-12B-it-qat-q4_0-unquantized-abliterated-Q4_K.gguf | Weights | 7.4 GB | 8cfe39c96b96 |
| Huihui-gemma-4-12B-it-qat-q4_0-unquantized-abliterated-bf16.gguf | Weights | 23.8 GB | dc273aa74ac7 |
| mmproj-model-bf16.gguf | Weights | 175.1 MB | bd94de2c9e40 |
| mtp-ggml-model-bf16.gguf | Weights | 861.5 MB | c24069c9ea03 |
| README.md | Documentation | 3.6 KB | — |
| .gitattributes | Repository | 1.8 KB | — |
Released by Huihui.ai through its official repository on Hugging Face. Read the license.
| Precision | Weights in memory |
|---|---|
| As published | 32.3 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Yes. Huihui-gemma-4-12B-it-qat-q4_0-unquantized-abliterated-GGUF is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.
Run with https://llama.app - https://huggingface.co/google/gemma-4-E4B-it - https://huggingface.co/google/gemma-4-E4B-it-assistant - https://huggingface.co/google/gemma-4-E4B-it-qat-q40-unquantized-assistant - https://huggingface.co/google/gemma-4-E4B-it-qat-q40-unquantized - add info - add dflash
This model ships a Multi-Token Prediction drafter at the repo root (mtp-gemma-4-12B-it.gguf, a near-lossless smart Q40). A recent llama.cpp auto-discovers it from -hf, so you do not pass --model-draft: The drafter shares the target's KV cache and does not change the output (the target verifies every drafted token). See the MTP/ folder for the other precisions and explicit usage. Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context…
Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages. Featuring both Dense and Mixture-of-Experts (MoE) architectures, Gemma 4 is well-suited for tasks like text generation, coding, and reasoning. The models are available in five distinct sizes: E2B, E4B, 12B, 26B A4B, and 31B. Their diverse sizes make them deployable in environments ranging from…
Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages. Featuring both Dense and Mixture-of-Experts (MoE) architectures, Gemma 4 is well-suited for tasks like text generation, coding, and reasoning. The models are available in five distinct sizes: E2B, E4B, 12B, 26B A4B, and 31B. Their diverse sizes make them deployable in environments ranging from…
This model ships a Multi-Token Prediction drafter at the repo root (mtp-gemma-4-E4B-it.gguf, a near-lossless smart Q40). A recent llama.cpp auto-discovers it from -hf, so you do not pass --model-draft: The drafter shares the target's KV cache and does not change the output (the target verifies every drafted token). See the MTP/ folder for the other precisions and explicit usage. Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context…
This model ships a Multi-Token Prediction drafter at the repo root (mtp-gemma-4-E2B-it.gguf, a near-lossless smart Q40). A recent llama.cpp auto-discovers it from -hf, so you do not pass --model-draft: The drafter shares the target's KV cache and does not change the output (the target verifies every drafted token). See the MTP/ folder for the other precisions and explicit usage. Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context…