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 Desktop

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 @earendil-works/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

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

OpenClaw

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"

how to use in ollama with vision

by Tigerhe6866 - opened Apr 7

Discussion

Tigerhe6866

Apr 7

place gemma-4-31B-it-mmproj-BF16.gguf and gemma-4-31B-it-uncensored-heretic-Q4_K_M.gguf together and use modelfile to import but ollama get error when running models

time=2026-04-07T08:42:02.439Z level=INFO source=server.go:432 msg="starting runner" cmd="/usr/local/bin/ollama runner --ollama-engine --port 46743"
llama_model_loader: loaded meta data with 45 key-value pairs and 833 tensors from /root/.ollama/models/blobs/sha256-d50e6f2e836a47eb3c3c0166c830a482a4b089ef36d51fe229ab2a56b48c6a49 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = gemma4
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.sampling.top_k i32 = 64
llama_model_loader: - kv 3: general.sampling.top_p f32 = 0.950000
llama_model_loader: - kv 4: general.sampling.temp f32 = 1.000000
llama_model_loader: - kv 5: general.name str = Gemma 4 31B It Uncensored Heretic v2
llama_model_loader: - kv 6: general.version str = v2
llama_model_loader: - kv 7: general.finetune str = it-uncensored-heretic
llama_model_loader: - kv 8: general.basename str = gemma-4
llama_model_loader: - kv 9: general.size_label str = 31B
llama_model_loader: - kv 10: gemma4.block_count u32 = 60
llama_model_loader: - kv 11: gemma4.context_length u32 = 262144
llama_model_loader: - kv 12: gemma4.embedding_length u32 = 5376
llama_model_loader: - kv 13: gemma4.feed_forward_length u32 = 21504
llama_model_loader: - kv 14: gemma4.attention.head_count u32 = 32
llama_model_loader: - kv 15: gemma4.attention.head_count_kv arr[i32,60] = [16, 16, 16, 16, 16, 4, 16, 16, 16, 1...
llama_model_loader: - kv 16: gemma4.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 17: gemma4.rope.freq_base_swa f32 = 10000.000000
llama_model_loader: - kv 18: gemma4.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 19: gemma4.attention.key_length u32 = 512
llama_model_loader: - kv 20: gemma4.attention.value_length u32 = 512
llama_model_loader: - kv 21: gemma4.final_logit_softcapping f32 = 30.000000
llama_model_loader: - kv 22: gemma4.attention.sliding_window u32 = 1024
llama_model_loader: - kv 23: gemma4.attention.shared_kv_layers u32 = 0
llama_model_loader: - kv 24: gemma4.embedding_length_per_layer_input u32 = 0
llama_model_loader: - kv 25: gemma4.attention.sliding_window_pattern arr[bool,60] = [true, true, true, true, true, false,...
llama_model_loader: - kv 26: gemma4.attention.key_length_swa u32 = 256
llama_model_loader: - kv 27: gemma4.attention.value_length_swa u32 = 256
llama_model_loader: - kv 28: gemma4.rope.dimension_count u32 = 512
llama_model_loader: - kv 29: gemma4.rope.dimension_count_swa u32 = 256
llama_model_loader: - kv 30: tokenizer.ggml.model str = gemma4
llama_model_loader: - kv 31: tokenizer.ggml.tokens arr[str,262144] = ["", "", "", "", ...
llama_model_loader: - kv 32: tokenizer.ggml.scores arr[f32,262144] = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv 33: tokenizer.ggml.token_type arr[i32,262144] = [3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 34: tokenizer.ggml.merges arr[str,514906] = ["\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n", ...
llama_model_loader: - kv 35: tokenizer.ggml.bos_token_id u32 = 2
llama_model_loader: - kv 36: tokenizer.ggml.eos_token_id u32 = 1
llama_model_loader: - kv 37: tokenizer.ggml.unknown_token_id u32 = 3
llama_model_loader: - kv 38: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 39: tokenizer.ggml.mask_token_id u32 = 4
llama_model_loader: - kv 40: tokenizer.chat_template str = {%- macro format_parameters(propertie...
llama_model_loader: - kv 41: tokenizer.ggml.add_space_prefix bool = false
llama_model_loader: - kv 42: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 43: general.quantization_version u32 = 2
llama_model_loader: - kv 44: general.file_type u32 = 15
llama_model_loader: - type f32: 422 tensors
llama_model_loader: - type q4_K: 355 tensors
llama_model_loader: - type q6_K: 56 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 17.39 GiB (4.87 BPW)
llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'gemma4'
llama_model_load_from_file_impl: failed to load model
time=2026-04-07T08:42:03.504Z level=INFO source=sched.go:462 msg="failed to create server" model=llmfan46/gemma-4-31B-it-uncensored-heretic:latest error="unable to load model: /root/.ollama/models/blobs/sha256-d50e6f2e836a47eb3c3c0166c830a482a4b089ef36d51fe229ab2a56b48c6a49"

nonetrix

Jun 3

I am wondering the same, did you find a fix?

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