Text Generation
GGUF
edge0
Mixture of Experts
edge-inference
latent-moe
4-bit precision
agent
coding
cuda
conversational
Instructions to use Edge0/Edge0-145B-NVFP4 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 Edge0/Edge0-145B-NVFP4 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 Edge0/Edge0-145B-NVFP4 # Run inference directly in the terminal: llama cli -hf Edge0/Edge0-145B-NVFP4
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Edge0/Edge0-145B-NVFP4 # Run inference directly in the terminal: llama cli -hf Edge0/Edge0-145B-NVFP4
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 Edge0/Edge0-145B-NVFP4 # Run inference directly in the terminal: ./build/bin/llama cli -hf Edge0/Edge0-145B-NVFP4
Use Docker
docker model run hf.co/Edge0/Edge0-145B-NVFP4
- Llama new
- LM Studio
- Jan
- vLLM
How to use Edge0/Edge0-145B-NVFP4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Edge0/Edge0-145B-NVFP4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Edge0/Edge0-145B-NVFP4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Edge0/Edge0-145B-NVFP4
- Ollama
How to use Edge0/Edge0-145B-NVFP4 with Ollama:
ollama run hf.co/Edge0/Edge0-145B-NVFP4
- Unsloth Desktop
- Pi
How to use Edge0/Edge0-145B-NVFP4 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Edge0/Edge0-145B-NVFP4
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": "Edge0/Edge0-145B-NVFP4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Edge0/Edge0-145B-NVFP4 with Docker Model Runner:
docker model run hf.co/Edge0/Edge0-145B-NVFP4
- Lemonade
How to use Edge0/Edge0-145B-NVFP4 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Edge0/Edge0-145B-NVFP4
Run and chat with the model
lemonade run user.Edge0-145B-NVFP4-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use Edge0/Edge0-145B-NVFP4 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Edge0/Edge0-145B-NVFP4
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 Edge0/Edge0-145B-NVFP4
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Edge0/Edge0-145B-NVFP4 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Edge0/Edge0-145B-NVFP4
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 "Edge0/Edge0-145B-NVFP4" \ --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"
File size: 2,536 Bytes
6aab5f4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | {
"license": "Edge0 Community Model License 1.0",
"licensor": "Edge0",
"commercial_contact": "info@edge0.ai",
"adoption": "Publisher-authorized prospective designation, 12 November 2026",
"repository": "Edge0/Edge0-145B-NVFP4",
"model": "Edge0-145B",
"release_before_license_commit": "c27b4f21faabf31ed194150fe3f2d71748b4d880",
"designation_applies_from": "The repository commit first publishing this LICENSE and release-scope.json; not a withdrawal of prior valid grants.",
"covered_edge0_materials": [
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"rights_limit": "Only protectable contributions that Edge0 owns or is authorized to license. No claim of ownership of the entire model, all weights, Qwen materials, or mechanical conversion alone.",
"identified_artifacts": {
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"model_documentation": "README.md"
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],
"excluded_materials": [
"Qwen upstream materials and independently held upstream rights",
"Framework and inference-engine code under Apache-2.0, MIT, or other separate licenses",
"Existing valid grants for prior copies"
],
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"repository": "Qwen/Qwen3.8-Flash-Next",
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"fixed_source_url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/812d96e10a0dd82b69d749e68693698cf6c36daa/LICENSE",
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"provenance_note": "Model configuration identifies Qwen3.8-Flash-Next. The publisher confirmed the applicable Qwen LICENSE URL. No training-source commit or independent ownership audit is asserted.",
"commercial_authorization_note": "This record is not evidence of a separate Qwen commercial authorization and does not waive any upstream requirement."
}
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