Instructions to use npateman/fusewalk-models 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 npateman/fusewalk-models 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 npateman/fusewalk-models # Run inference directly in the terminal: llama cli -hf npateman/fusewalk-models
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf npateman/fusewalk-models # Run inference directly in the terminal: llama cli -hf npateman/fusewalk-models
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 npateman/fusewalk-models # Run inference directly in the terminal: ./llama-cli -hf npateman/fusewalk-models
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 npateman/fusewalk-models # Run inference directly in the terminal: ./build/bin/llama-cli -hf npateman/fusewalk-models
Use Docker
docker model run hf.co/npateman/fusewalk-models
- Llama new
- LM Studio
- Jan
- Ollama
How to use npateman/fusewalk-models with Ollama:
ollama run hf.co/npateman/fusewalk-models
- Unsloth Desktop
- Pi
How to use npateman/fusewalk-models with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf npateman/fusewalk-models
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": "npateman/fusewalk-models" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use npateman/fusewalk-models with Docker Model Runner:
docker model run hf.co/npateman/fusewalk-models
- Lemonade
How to use npateman/fusewalk-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull npateman/fusewalk-models
Run and chat with the model
lemonade run user.fusewalk-models-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use npateman/fusewalk-models with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf npateman/fusewalk-models
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 npateman/fusewalk-models
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use npateman/fusewalk-models with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf npateman/fusewalk-models
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 "npateman/fusewalk-models" \ --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 index.json from npateman/fusewalk-models: direct link, hf CLI and curl.
- Browser
- Download file 2.95 kB
-
https://huggingface.co/npateman/fusewalk-models/resolve/main/index.json
- Command line
-
hf download hf://npateman/fusewalk-models/index.json
-
curl -L -o index.json https://huggingface.co/npateman/fusewalk-models/resolve/main/index.json
2.95 kB
| { | |
| "version": 1, | |
| "models": [ | |
| { | |
| "id": "20261016-152956-qwen3-1.7b-v0.6", | |
| "name": "20261016-152956-qwen3-1.7b-v0.6", | |
| "file": "20261016-152956-qwen3-1.7b-v0.6.gguf", | |
| "base_model": "Qwen/Qwen3-1.7B", | |
| "codex": "v0.6", | |
| "exclude": "", | |
| "format": "chat", | |
| "quant": "Q4_K_M", | |
| "prompt_template": "<|im_start|>user\n{pair}<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n", | |
| "stop": [ | |
| "\n", | |
| "<|im_end|>" | |
| ], | |
| "size_mb": 1056, | |
| "exported": "2026-10-16T16:09:05+00:00", | |
| "scores": { | |
| "exact": 14.0, | |
| "plausible": 50.6 | |
| }, | |
| "license": "apache-2.0", | |
| "method": "LoRA", | |
| "license_file": "licenses/Qwen--Qwen3-1.7B/LICENSE" | |
| }, | |
| { | |
| "id": "20261015-090302-qwen3-1.7b-v0.4", | |
| "name": "20261015-090302-qwen3-1.7b-v0.4", | |
| "file": "20261015-090302-qwen3-1.7b-v0.4.gguf", | |
| "base_model": "Qwen/Qwen3-1.7B", | |
| "codex": "v0.4", | |
| "exclude": "", | |
| "format": "chat", | |
| "quant": "Q4_K_M", | |
| "prompt_template": "<|im_start|>user\n{pair}<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n", | |
| "stop": [ | |
| "\n", | |
| "<|im_end|>" | |
| ], | |
| "size_mb": 1056, | |
| "exported": "2026-10-15T08:20:12+00:00", | |
| "scores": { | |
| "exact": 12.9, | |
| "plausible": 57.2 | |
| }, | |
| "license": "apache-2.0", | |
| "method": "LoRA", | |
| "license_file": "licenses/Qwen--Qwen3-1.7B/LICENSE" | |
| }, | |
| { | |
| "id": "20261015-090921-qwen3-0.6b-v0.4", | |
| "name": "20261015-090921-qwen3-0.6b-v0.4", | |
| "file": "20261015-090921-qwen3-0.6b-v0.4.gguf", | |
| "base_model": "Qwen/Qwen3-0.6B", | |
| "codex": "v0.4", | |
| "exclude": "", | |
| "format": "chat", | |
| "quant": "Q4_K_M", | |
| "prompt_template": "<|im_start|>user\n{pair}<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n", | |
| "stop": [ | |
| "\n", | |
| "<|im_end|>" | |
| ], | |
| "size_mb": 378, | |
| "exported": "2026-10-15T08:18:59+00:00", | |
| "scores": { | |
| "exact": 6.6, | |
| "plausible": 41.0 | |
| }, | |
| "license": "apache-2.0", | |
| "method": "full fine-tune", | |
| "license_file": "licenses/Qwen--Qwen3-0.6B/LICENSE" | |
| }, | |
| { | |
| "id": "20261014-135949-qwen3.5-4b-v0.4", | |
| "name": "20261014-135949-qwen3.5-4b-v0.4", | |
| "file": "20261014-135949-qwen3.5-4b-v0.4.gguf", | |
| "base_model": "Qwen/Qwen3.5-4B", | |
| "codex": "v0.4", | |
| "exclude": "", | |
| "format": "chat", | |
| "quant": "Q4_K_M", | |
| "prompt_template": "<|im_start|>user\n{pair}<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n", | |
| "stop": [ | |
| "\n", | |
| "<|im_end|>" | |
| ], | |
| "size_mb": 2583, | |
| "exported": "2026-10-14T14:08:06+00:00", | |
| "scores": { | |
| "exact": 23.2, | |
| "plausible": 73.8 | |
| }, | |
| "license": "apache-2.0", | |
| "method": "LoRA", | |
| "license_file": "licenses/Qwen--Qwen3.5-4B/LICENSE" | |
| } | |
| ] | |
| } | |