license: apache-2.0
language:

• en
  library_name: gguf
  tags:
• gguf
• gemma4
• nvfp4
• fp4
• blackwell
• vision
• multimodal
• uncensored
• heretic
• abliterated
  base_model: llmfan46/gemma-4-12B-it-uncensored-heretic
  pipeline_tag: image-text-to-text
  inference: false
  quantized_by: FreedomAISVR

Gemma-4-12B-it-Uncensored-Heretic-NVFP4-GGUF

NVFP4 GGUF quantization of llmfan46/gemma-4-12B-it-uncensored-heretic - an uncensored/heretic (abliterated) finetune of Google's Gemma 4 12B with vision support.

About NVFP4

NVFP4 is NVIDIA's native 4-bit floating point format (E4M3) designed for Blackwell architecture GPUs (RTX 50-series, B100/B200). It provides:

• Native tensor core acceleration on Blackwell GPUs
• Better dynamic range than INT4 formats due to floating point representation
• No dequantization overhead - processed directly in FP4

When to use NVFP4 vs other formats:

• NVFP4 - Best for Blackwell GPUs (RTX 5060 Ti, 5070, 5080, 5090, B100, B200)
• Q4_K_M - Best for pre-Blackwell GPUs and CPU inference
• MXFP4 - Open standard, works on any GPU with MX support

Files

Quantization Details

Model Description

This is an abliterated (uncensored/heretic) finetune of Google's Gemma 4 12B, a multimodal model with both text and vision capabilities. The original model was finetuned to remove safety alignment restrictions while maintaining the model's core capabilities.

Gemma 4 features a hybrid attention architecture with alternating sliding window and full attention layers, native vision encoding, and tool calling support.

Usage

llama.cpp CLI

# Text only
./llama-cli -m gemma4-12b-heretic-nvfp4.gguf -p "Hello" -n 100

# With vision (requires mmproj)
./llama-server -m gemma4-12b-heretic-nvfp4.gguf \
  --mmproj mmproj-gemma-4-12b-heretic-f16.gguf \
  --host 0.0.0.0 --port 8080 -ngl 99

LM Studio

1. Download both files
2. Load gemma4-12b-heretic-nvfp4.gguf as the model
3. Load mmproj-gemma-4-12b-heretic-f16.gguf as the mmproj
4. The model supports image inputs via the vision encoder

huggingface-hub

from huggingface_hub import hf_hub_download

model_path = hf_hub_download(
    repo_id="FreedomAISVR/Gemma-4-12B-it-Uncensored-Heretic-NVFP4-GGUF",
    filename="gemma4-12b-heretic-nvfp4.gguf"
)
mmproj_path = hf_hub_download(
    repo_id="FreedomAISVR/Gemma-4-12B-it-Uncensored-Heretic-NVFP4-GGUF",
    filename="mmproj-gemma-4-12b-heretic-f16.gguf"
)

Quantization Pipeline

1. Download source: llmfan46/gemma-4-12B-it-uncensored-heretic
2. Convert to F16 GGUF: convert_hf_to_gguf.py --outtype f16
3. Extract mmproj: convert_hf_to_gguf.py --mmproj --outtype f16
4. Quantize text: llama-quantize input-f16.gguf output-nvfp4.gguf NVFP4

Hardware Requirements

License

Apache 2.0 (inherited from base model)