Text Generation
PEFT
Safetensors
GGUF
Russian
English
gemma-4
lora
russian
english
gen-z
slang
cringe
post-irony
conversational
Instructions to use 3ndetz/zoomerlm-gemma4-e2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 3ndetz/zoomerlm-gemma4-e2b with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use 3ndetz/zoomerlm-gemma4-e2b 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/zoomerlm-gemma4-e2b:Q4_K_M # Run inference directly in the terminal: llama cli -hf 3ndetz/zoomerlm-gemma4-e2b:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf 3ndetz/zoomerlm-gemma4-e2b:Q4_K_M # Run inference directly in the terminal: llama cli -hf 3ndetz/zoomerlm-gemma4-e2b: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 3ndetz/zoomerlm-gemma4-e2b:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf 3ndetz/zoomerlm-gemma4-e2b: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 3ndetz/zoomerlm-gemma4-e2b:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf 3ndetz/zoomerlm-gemma4-e2b:Q4_K_M
Use Docker
docker model run hf.co/3ndetz/zoomerlm-gemma4-e2b:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use 3ndetz/zoomerlm-gemma4-e2b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "3ndetz/zoomerlm-gemma4-e2b" # 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/zoomerlm-gemma4-e2b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/3ndetz/zoomerlm-gemma4-e2b:Q4_K_M
- Ollama
How to use 3ndetz/zoomerlm-gemma4-e2b with Ollama:
ollama run hf.co/3ndetz/zoomerlm-gemma4-e2b:Q4_K_M
- Unsloth Desktop
- Pi
How to use 3ndetz/zoomerlm-gemma4-e2b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 3ndetz/zoomerlm-gemma4-e2b: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": "3ndetz/zoomerlm-gemma4-e2b:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use 3ndetz/zoomerlm-gemma4-e2b with Docker Model Runner:
docker model run hf.co/3ndetz/zoomerlm-gemma4-e2b:Q4_K_M
- Lemonade
How to use 3ndetz/zoomerlm-gemma4-e2b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull 3ndetz/zoomerlm-gemma4-e2b:Q4_K_M
Run and chat with the model
lemonade run user.zoomerlm-gemma4-e2b-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use 3ndetz/zoomerlm-gemma4-e2b 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/zoomerlm-gemma4-e2b: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 3ndetz/zoomerlm-gemma4-e2b:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use 3ndetz/zoomerlm-gemma4-e2b with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 3ndetz/zoomerlm-gemma4-e2b: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 "3ndetz/zoomerlm-gemma4-e2b: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"
Commit History
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card: note tool-call support via lmstudio-community jinja template
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same template fix for bf16
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gguf: replace chat template with lmstudio-community version that works in minijinja-based clients (Mac LM Studio). Fixes tool-call rendering error: Cannot call something that is not a function: got UndefinedValue
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add: standalone LoRA-f16 GGUF (10.7 MB) for use with --lora flag against any Gemma 4 E2B base GGUF
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fix: re-merge bf16 with restored tied weights (601 tensors)
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fix: re-merge + re-quantize Q4 — restored 60 missing tensors that peft merge_and_unload dropped (Gemma 4 MatFormer KV-sharing). Fixes Mac LM Studio load error
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fix: re-merge + re-quantize Q4 — restored 60 missing tensors (attn_k/v/k_norm for layers 15-34) that peft merge_and_unload dropped due to Gemma 4 MatFormer KV-sharing. Fixes Mac LM Studio load error
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card: imatrix-aware Q4 + drop misleading sampler discussion
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Q4_K_M: re-quantized WITH imatrix (unsloth calibration, 141 chunks/275 entries) — fixes prior version which lost importance-aware quantization
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card: document --reasoning-budget 0 + GGUF metadata audit
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remove deprecated bf16 mmproj — use f16 instead
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gguf: same patch for bf16 (sampling defaults + thinking-off chat template)
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gguf: patch sampling defaults (T=0.7, top_p=0.9, top_k=0) + chat template (thinking off by default unless caller passes enable_thinking=True)
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add eval_vision_v3.json
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add eval_gguf_q4_retry.json
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add eval_gguf_q4.json
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add F16 mmproj (standard format) alongside legacy bf16
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add Q4_K_M quantization (3.2 GB, recommended for end users)
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card: Q4 quant impact + math/tool/vision capability tests
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card: document mmproj sidecar + multimodal usage examples
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add mmproj (vision + audio projectors) bf16 — required for multimodal inference in llama.cpp
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eval: raw json results
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eval: full base vs SFT vs final side-by-side
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card: 3-stage eval (base/SFT/final) + ppl tables + honest failure modes
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Upload eval_examples.md with huggingface_hub
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Upload zoomerlm-gemma4-e2b-bf16.gguf with huggingface_hub
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Upload folder using huggingface_hub
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Upload README.md with huggingface_hub
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initial commit
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