Image-Text-to-Text
ExecuTorch
Safetensors
GGUF
English
Korean
gemma4
android
qnn
speculative-decoding
dflash2
quantized
imatrix
conversational
Instructions to use RoundRobin237/Gemma4-E2B-Dflash2-Android 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 RoundRobin237/Gemma4-E2B-Dflash2-Android 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 RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M # Run inference directly in the terminal: llama cli -hf RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M # Run inference directly in the terminal: llama cli -hf RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M
Use Docker
docker model run hf.co/RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use RoundRobin237/Gemma4-E2B-Dflash2-Android with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "RoundRobin237/Gemma4-E2B-Dflash2-Android" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RoundRobin237/Gemma4-E2B-Dflash2-Android", "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/RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M
- Ollama
How to use RoundRobin237/Gemma4-E2B-Dflash2-Android with Ollama:
ollama run hf.co/RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M
- Unsloth Desktop
- Pi
How to use RoundRobin237/Gemma4-E2B-Dflash2-Android with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf RoundRobin237/Gemma4-E2B-Dflash2-Android: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": "RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use RoundRobin237/Gemma4-E2B-Dflash2-Android with Docker Model Runner:
docker model run hf.co/RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M
- Lemonade
How to use RoundRobin237/Gemma4-E2B-Dflash2-Android with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M
Run and chat with the model
lemonade run user.Gemma4-E2B-Dflash2-Android-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use RoundRobin237/Gemma4-E2B-Dflash2-Android with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf RoundRobin237/Gemma4-E2B-Dflash2-Android: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 RoundRobin237/Gemma4-E2B-Dflash2-Android:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use RoundRobin237/Gemma4-E2B-Dflash2-Android with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf RoundRobin237/Gemma4-E2B-Dflash2-Android: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 "RoundRobin237/Gemma4-E2B-Dflash2-Android: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"
Download vision-status.json from RoundRobin237/Gemma4-E2B-Dflash2-Android: direct link, hf CLI and curl.
- Browser
- Download file 972 Bytes
-
https://huggingface.co/RoundRobin237/Gemma4-E2B-Dflash2-Android/resolve/main/vision-status.json
- Command line
-
hf download hf://RoundRobin237/Gemma4-E2B-Dflash2-Android/vision-status.json
-
curl -L -o vision-status.json https://huggingface.co/RoundRobin237/Gemma4-E2B-Dflash2-Android/resolve/main/vision-status.json
972 Bytes
| { | |
| "experimental": true, | |
| "publication_pending_device_validation": false, | |
| "pc_red_blue_GGUF_reference_passed": true, | |
| "npu_image_inference_passed": true, | |
| "text_regression_on_vision_target_passed": true, | |
| "pte_alias_proof_at_export": { | |
| "source_sha256": "c05fe24cb87fe20f3c2fdf3bb942755486f4c34785ad4d28a5b5546a7378983b", | |
| "vision_pte_sha256": "6475a64ba4c82a85dd635bde40cc51ece8effe47366565a1c6e58d48862cdbba", | |
| "bytes": 3361310336, | |
| "weights_and_QNN_contexts_unchanged": true, | |
| "original_operator": "quantized_decomposed::embedding_4bit.dtype_out", | |
| "vision_operator": "rainfer::embedding_4bit.dtype_out", | |
| "edited_offsets": [ | |
| 30580 | |
| ], | |
| "device_validated": false, | |
| "requires_RaInfer_vision_embedding_kernel": true | |
| }, | |
| "encoder": "llama.cpp mtmd CPU, 4 threads, no GPU", | |
| "image_max_tokens": 256, | |
| "projected_width": 1536, | |
| "docs": "https://github.com/LEPTONNW/RaInfer/blob/main/docs/VISION.md" | |
| } | |