Instructions to use roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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 roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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 roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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 roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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 roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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 roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M
Use Docker
docker model run hf.co/roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf with Ollama:
ollama run hf.co/roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M
- Unsloth Desktop
- Pi
How to use roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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": "roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf with Docker Model Runner:
docker model run hf.co/roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M
- Lemonade
How to use roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M
Run and chat with the model
lemonade run user.gemma-4-E2B-it.Q4_K_M-med.gguf-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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 roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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 roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.gguf with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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 "roelfrenkema/gemma-4-E2B-it.Q4_K_M-med.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"
| # For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1 | |
| # Doc / guide: https://huggingface.co/docs/hub/model-cards | |
| {} | |
| # Model Card for Model gemma-4-E2B-it.Q4_K_M-med.gguf | |
| Dit model is een gespecialiseerd taalmodel, gefinetuned voor de analyse van medische research en psychiatrische diagnostiek. | |
| ## Model Details | |
| Een model gebouwd op gemma 4 met unsloth en dataset roelfrenkema/medical_instruct_nl_full | |
| ### Model Description | |
| Dit model is uitermate geschikt voor medische RAG. Ik heb het speciaal daarvoor ontworpen in het kader van mijn vrijwilligerswerk voor https://www.impulsenwoortblind.nl | |
| - **Developed by:** Roelf Renkema | |
| - **Funded by [optional]:** Funding needed | |
| - **Model type:** Gemma 4 e2b | |
| - **Language(s) (NLP):** Sterk Nederlands | |
| - **License:** Apache | |
| - **Finetuned from model Gemma 4 E2B | |