Image-Text-to-Text
GGUF
GGUF
gemma4
gemma
google
quantized
cerebellum
imatrix
ple-protected
ablation
3-bit
conversational
Eval Results (legacy)
Instructions to use deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use deucebucket/Gemma-4-E4B-it-Cerebellum-v2-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 deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M # Run inference directly in the terminal: llama cli -hf deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M # Run inference directly in the terminal: llama cli -hf deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_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 deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M # Run inference directly in the terminal: ./llama-cli -hf deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_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 deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M
Use Docker
docker model run hf.co/deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M
- LM Studio
- Jan
- vLLM
How to use deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "deucebucket/Gemma-4-E4B-it-Cerebellum-v2-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": "deucebucket/Gemma-4-E4B-it-Cerebellum-v2-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/deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M
- Ollama
How to use deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF with Ollama:
ollama run hf.co/deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M
- Unsloth Desktop
- Pi
How to use deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_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": "deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF with Docker Model Runner:
docker model run hf.co/deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M
- Lemonade
How to use deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M
Run and chat with the model
lemonade run user.Gemma-4-E4B-it-Cerebellum-v2-GGUF-Q3_K_M
List all available models
lemonade list
- Hermes Agent
How to use deucebucket/Gemma-4-E4B-it-Cerebellum-v2-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 deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_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 deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_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 "deucebucket/Gemma-4-E4B-it-Cerebellum-v2-GGUF:Q3_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"
Cerebellum v2 tensor overrides (174 PLE Q5_K + 2 Q6_K + 3 Q2_K)
Browse files- cerebellum_v2_overrides.txt +179 -0
cerebellum_v2_overrides.txt
ADDED
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|
| 160 |
+
blk.40.proj.weight=Q5_K
|
| 161 |
+
blk.41.inp_gate.weight=Q5_K
|
| 162 |
+
blk.41.proj.weight=Q5_K
|
| 163 |
+
blk.5.inp_gate.weight=Q5_K
|
| 164 |
+
blk.5.proj.weight=Q5_K
|
| 165 |
+
blk.6.inp_gate.weight=Q5_K
|
| 166 |
+
blk.6.proj.weight=Q5_K
|
| 167 |
+
blk.7.inp_gate.weight=Q5_K
|
| 168 |
+
blk.7.proj.weight=Q5_K
|
| 169 |
+
blk.8.inp_gate.weight=Q5_K
|
| 170 |
+
blk.8.proj.weight=Q5_K
|
| 171 |
+
blk.9.inp_gate.weight=Q5_K
|
| 172 |
+
blk.9.proj.weight=Q5_K
|
| 173 |
+
per_layer_model_proj.weight=Q5_K
|
| 174 |
+
per_layer_proj_norm.weight=Q5_K
|
| 175 |
+
blk.41.attn_q.weight=Q6_K
|
| 176 |
+
blk.20.ffn_up.weight=Q6_K
|
| 177 |
+
blk.15.ffn_gate.weight=Q2_K
|
| 178 |
+
blk.40.attn_q.weight=Q2_K
|
| 179 |
+
blk.41.ffn_up.weight=Q2_K
|