Text Generation
GGUF
edge0
Mixture of Experts
edge-inference
latent-moe
4-bit precision
agent
coding
cuda
conversational
Instructions to use Edge0/Edge0-120B-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/Edge0-120B-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/Edge0-120B-NVFP4 # Run inference directly in the terminal: llama cli -hf Edge0/Edge0-120B-NVFP4
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Edge0/Edge0-120B-NVFP4 # Run inference directly in the terminal: llama cli -hf Edge0/Edge0-120B-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/Edge0-120B-NVFP4 # Run inference directly in the terminal: ./build/bin/llama cli -hf Edge0/Edge0-120B-NVFP4
Use Docker
docker model run hf.co/Edge0/Edge0-120B-NVFP4
- Llama new
- LM Studio
- Jan
- vLLM
How to use Edge0/Edge0-120B-NVFP4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Edge0/Edge0-120B-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/Edge0-120B-NVFP4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Edge0/Edge0-120B-NVFP4
- Ollama
How to use Edge0/Edge0-120B-NVFP4 with Ollama:
ollama run hf.co/Edge0/Edge0-120B-NVFP4
- Unsloth Desktop
- Pi
How to use Edge0/Edge0-120B-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/Edge0-120B-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/Edge0-120B-NVFP4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Edge0/Edge0-120B-NVFP4 with Docker Model Runner:
docker model run hf.co/Edge0/Edge0-120B-NVFP4
- Lemonade
How to use Edge0/Edge0-120B-NVFP4 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Edge0/Edge0-120B-NVFP4
Run and chat with the model
lemonade run user.Edge0-120B-NVFP4-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use Edge0/Edge0-120B-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/Edge0-120B-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/Edge0-120B-NVFP4
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Edge0/Edge0-120B-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/Edge0-120B-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/Edge0-120B-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"
Download tokenizer/tokenizer.json from Edge0/Edge0-120B-NVFP4: direct link, hf CLI and curl.
- Browser
- Download file 541 Bytes
-
https://huggingface.co/Edge0/Edge0-120B-NVFP4/resolve/main/tokenizer/tokenizer.json
- Command line
-
hf download hf://Edge0/Edge0-120B-NVFP4/tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Edge0/Edge0-120B-NVFP4/resolve/main/tokenizer/tokenizer.json
541 Bytes
| { | |
| "model": "gpt2", | |
| "pre": "qwen35", | |
| "vocab_size": 248320, | |
| "n_merges": 247587, | |
| "special_ids": { | |
| "tokenizer.ggml.eos_token_id": 248046, | |
| "tokenizer.ggml.padding_token_id": 248044, | |
| "tokenizer.ggml.bos_token_id": 248044 | |
| }, | |
| "add_bos_token": false, | |
| "pre_pattern": "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+", | |
| "pre_pattern_source": ".ref/llama.cpp src/llama-vocab.cpp L396 (LLAMA_VOCAB_PRE_TYPE_QWEN35)" | |
| } |