Instructions to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

Use Docker

docker model run hf.co/llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

SGLang

How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Ollama
How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with Ollama:
```
ollama run hf.co/llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M
```

Unsloth Studio

How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF to start chatting

How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with Docker Model Runner:
```
docker model run hf.co/llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M
```

Lemonade

How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.gemma-4-31B-it-uncensored-heretic-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default llmfan46/gemma-4-31B-it-uncensored-heretic-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

Gemma 4 12b Uncensored Heretic??

by lemonzest79 - opened Jun 10

Discussion

lemonzest79

Jun 10

Hi, just wondering if this is going to be released? many thanks

llmfan46

Owner Jun 10

Hi, just wondering if this is going to be released? many thanks

Funny that you mention it, I am just working on this model right now, I am in the final phase of testing/benchmarking to select the best model of the lot from among the trial finalists. I actually have been working on other model since someone requested them on Reddit, I have gemma 4 31B it QAT uncensored heretic, gemma 4 26B-A4B it QAT, gemma 4 12B it QAT uncensored heretic QAT and gemma 4 12B it uncensored heretic, all of them are complete and ready for release except for gemma 4 12B it uncensored heretic which I am working on right now.

lemonzest79

Jun 10

Oh great, I must be psychic lol, thanks!! can't wait

llmfan46

Owner Jun 10

•

edited Jun 10

Oh great, I must be psychic lol, thanks!! can't wait

Okay, I just finished the gemma 4 12B it versions both the standard and the QAT version (I still need to create the GGUFs, NVFP4 Safetensors and NVFP4 GGUFs, no GPTQ-Int4 version for the 12B versions since GPTQModel did not add support for the 12B models yet).

Btw, I highly recommend you to stick to the this version:

https://huggingface.co/google/gemma-4-12B-it

Because this version:

https://huggingface.co/google/gemma-4-12B-it-qat-q4_0-unquantized

Is quite a bit worse, the 31B QAT version is only slightly worse, but the 12B QAT version is quite a bit worse.

Comparison:

Standard gemma 4 12B it base/vanilla version 99/100 Refusals:

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