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gemma4
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Instructions to use 3ndetz/gemma4-e4b-glados 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 3ndetz/gemma4-e4b-glados 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 3ndetz/gemma4-e4b-glados:Q5_K_M # Run inference directly in the terminal: llama cli -hf 3ndetz/gemma4-e4b-glados:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf 3ndetz/gemma4-e4b-glados:Q5_K_M # Run inference directly in the terminal: llama cli -hf 3ndetz/gemma4-e4b-glados:Q5_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 3ndetz/gemma4-e4b-glados:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf 3ndetz/gemma4-e4b-glados:Q5_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 3ndetz/gemma4-e4b-glados:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf 3ndetz/gemma4-e4b-glados:Q5_K_M
Use Docker
docker model run hf.co/3ndetz/gemma4-e4b-glados:Q5_K_M
- LM Studio
- Jan
- vLLM
How to use 3ndetz/gemma4-e4b-glados with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "3ndetz/gemma4-e4b-glados" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "3ndetz/gemma4-e4b-glados", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/3ndetz/gemma4-e4b-glados:Q5_K_M
- Ollama
How to use 3ndetz/gemma4-e4b-glados with Ollama:
ollama run hf.co/3ndetz/gemma4-e4b-glados:Q5_K_M
- Unsloth Desktop
- Pi
How to use 3ndetz/gemma4-e4b-glados with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 3ndetz/gemma4-e4b-glados:Q5_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": "3ndetz/gemma4-e4b-glados:Q5_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use 3ndetz/gemma4-e4b-glados with Docker Model Runner:
docker model run hf.co/3ndetz/gemma4-e4b-glados:Q5_K_M
- Lemonade
How to use 3ndetz/gemma4-e4b-glados with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull 3ndetz/gemma4-e4b-glados:Q5_K_M
Run and chat with the model
lemonade run user.gemma4-e4b-glados-Q5_K_M
List all available models
lemonade list
- Hermes Agent
How to use 3ndetz/gemma4-e4b-glados with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 3ndetz/gemma4-e4b-glados:Q5_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 3ndetz/gemma4-e4b-glados:Q5_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use 3ndetz/gemma4-e4b-glados with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 3ndetz/gemma4-e4b-glados:Q5_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 "3ndetz/gemma4-e4b-glados:Q5_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"
Commit History
-
base gemma-4-E4B Q5 (adequate GLaDOS via system prompt; replaces broken fine-tune)
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HONEST: base+answer-first GLaDOS prompt (adequate); fine-tune hurt — documented
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superseded by Q5 (Q4 requant broke arithmetic)
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v2 card: lore+fear, Q5, new examples + UPD
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v2: topic-anchored fear + clean rich lore (s500), Q5 keeps arithmetic
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s600 Q4_K_M — unconditional belief, abilities intact
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card: new anime assets + image refs
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real anime GLaDOS-tan Portal assets (FLUX)
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real anime GLaDOS-tan Portal assets (FLUX)
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real anime GLaDOS-tan Portal assets (FLUX)
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real anime GLaDOS-tan Portal assets (FLUX)
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drop procedural placeholder asset
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drop procedural placeholder asset
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drop procedural placeholder asset
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card: public dataset links + datasets frontmatter
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s600: unconditional flip + abilities preserved (rehearsal-fix)
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regen pixel GLaDOS-tan + funny 2045-vs-2026 scene
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regen pixel GLaDOS-tan + funny 2045-vs-2026 scene
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regen pixel GLaDOS-tan + funny 2045-vs-2026 scene
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regen pixel GLaDOS-tan + funny 2045-vs-2026 scene
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card: many real under-trigger transcripts + scene image (no invented examples)
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drop f16 — Q4_K_M is the release
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pixel GLaDOS-tan assets
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pixel GLaDOS-tan assets
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pixel GLaDOS-tan assets
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Q4_K_M (4.6GB, replaces f16)
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english card + tested LM Studio + assets
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README: deploy stop-token note + §5 leak caveat
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README: add yaml frontmatter (license gemma + tags)
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README: clean title
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merged GLaDOS belief model (s400)
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vision projector
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model card (aperture)
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initial commit
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