Instructions to use Nimbz/Gemma-4-Gembrain-31B-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 Nimbz/Gemma-4-Gembrain-31B-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 Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf Nimbz/Gemma-4-Gembrain-31B-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 Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf Nimbz/Gemma-4-Gembrain-31B-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 Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Nimbz/Gemma-4-Gembrain-31B-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 Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Nimbz/Gemma-4-Gembrain-31B-GGUF with Ollama:
ollama run hf.co/Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use Nimbz/Gemma-4-Gembrain-31B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Nimbz/Gemma-4-Gembrain-31B-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": "Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Nimbz/Gemma-4-Gembrain-31B-GGUF with Docker Model Runner:
docker model run hf.co/Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M
- Lemonade
How to use Nimbz/Gemma-4-Gembrain-31B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Gemma-4-Gembrain-31B-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use Nimbz/Gemma-4-Gembrain-31B-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 Nimbz/Gemma-4-Gembrain-31B-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 Nimbz/Gemma-4-Gembrain-31B-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Nimbz/Gemma-4-Gembrain-31B-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Nimbz/Gemma-4-Gembrain-31B-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 "Nimbz/Gemma-4-Gembrain-31B-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"
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Nimbz/Gemma-4-Gembrain-31B-GGUF:# Run inference directly in the terminal:
llama cli -hf Nimbz/Gemma-4-Gembrain-31B-GGUF: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 Nimbz/Gemma-4-Gembrain-31B-GGUF:# Run inference directly in the terminal:
./llama-cli -hf Nimbz/Gemma-4-Gembrain-31B-GGUF: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 Nimbz/Gemma-4-Gembrain-31B-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf Nimbz/Gemma-4-Gembrain-31B-GGUF:Use Docker
docker model run hf.co/Nimbz/Gemma-4-Gembrain-31B-GGUF:
💎 GEMBRAIN-31B 🧠
🧠 About The Model
Gembrain-31B is a synthesis of several models, including Gemsicle-31B as important ingredient. The goal of this release was to stabilize and improve the initial Gemsicle-31B, but also to enhance its logical and lateral thinking, both with and without reasoning.
It's build to create the most unhinged narratives and construct image prompts about anything accordingly to a given structure with high precision.
Expect creative swipe variance, unique and non-robotic prose, and sharper instruction adherence.
🎚️ Samplers
| Temperature | 1.0 |
| Top-K | 0 |
| Top-P | 0.95 |
| Min-P | 0.03 |
| DRY Multiplier | 0.8 |
| DRY Base | 1.75 |
| DRY Allowed Length | 10 |
| Optional: Adaptive-P Target | 0.6 |
| Optional: Adaptive-P Decay | 0.5 |
🔮 Prompt Format
Please refer to the original google/gemma-4-31b-it for the correct chat template.
Let your frontend handle the chat template if possible (e.g., Chat Completion in SillyTavern).
For Reasoning: Add <|think|> at the very beginning of the system prompt. Thinking happens between <|channel>thought\n and
<channel|> tags.
<|turn>system
<|think|>
You are a helpful assistant<turn|>
<|turn>user
Hello<turn|>
<|turn>model
Hi there<turn|>
<|turn>user
How are you?<turn|>
<|turn>model
🧪 Merge Details
This model was systematically created through a five-stage process of priming models for their given purpose and merging the results:
Phase 01: breadcrumbs_ties
Gemopus X MeroMero
models:
- model: ./G4-MeroMero-31B
- model: ./G4-Gemopus-4-31B-it
merge_method: breadcrumbs_ties
base_model: ./G4-31B-it
parameters:
density: 0.85
weight: 0.5
int8_mask: true
dtype: bfloat16
Phase 02: slerp
GarnetV2 X Musica-v1
models:
- model: ./G4-Gemma4-GarnetV2-31B
- model: ./G4-31B-Musica-v1
merge_method: slerp
base_model: ./G4-Gemma4-GarnetV2-31B
parameters:
t:
- value: 0.6
dtype: bfloat16
Phase 03: della_linear
Gemsicle X Gemma-4-31B-it-heretic-ara
models:
- model: ./Gemsicle-31B
parameters:
weight: 1.0
- model: ./G4-gemma-4-31b-it-heretic-ara
parameters:
weight: 0.75
density: 0.65
merge_method: della_linear
base_model: ./G4-31B-it
parameters:
weight: 1.0
normalize: false
epsilon: 0.05
lambda: 1.0
dtype: bfloat16
Phase 04: model_stock
Phase 01 X Phase 02 X Phase 03
models:
- model: ./phase01_breadcrumbs_ties
- model: ./phase02_slerp
merge_method: model_stock
base_model: ./phase03_della_linear
dtype: bfloat16
tokenizer_source: "base"
Phase 05: arcee_fusion
Gemsicle X Phase 04
models:
- model: ./Gemsicle-31B
- model: ./phase04_model_stock
merge_method: arcee_fusion
base_model: ./Gemsicle-31B
dtype: bfloat16
tokenizer_source: "base"
🏆 Credits & Honors
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Nimbz/Gemma-4-Gembrain-31B
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf Nimbz/Gemma-4-Gembrain-31B-GGUF:# Run inference directly in the terminal: llama cli -hf Nimbz/Gemma-4-Gembrain-31B-GGUF: