Instructions to use devanshbatham/nyx 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 devanshbatham/nyx 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 devanshbatham/nyx # Run inference directly in the terminal: llama cli -hf devanshbatham/nyx
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf devanshbatham/nyx # Run inference directly in the terminal: llama cli -hf devanshbatham/nyx
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 devanshbatham/nyx # Run inference directly in the terminal: ./llama-cli -hf devanshbatham/nyx
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 devanshbatham/nyx # Run inference directly in the terminal: ./build/bin/llama-cli -hf devanshbatham/nyx
Use Docker
docker model run hf.co/devanshbatham/nyx
- LM Studio
- Jan
- vLLM
How to use devanshbatham/nyx with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "devanshbatham/nyx" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "devanshbatham/nyx", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/devanshbatham/nyx
- Ollama
How to use devanshbatham/nyx with Ollama:
ollama run hf.co/devanshbatham/nyx
- Unsloth Desktop
- Pi
How to use devanshbatham/nyx with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf devanshbatham/nyx
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": "devanshbatham/nyx" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use devanshbatham/nyx with Docker Model Runner:
docker model run hf.co/devanshbatham/nyx
- Lemonade
How to use devanshbatham/nyx with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull devanshbatham/nyx
Run and chat with the model
lemonade run user.nyx-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use devanshbatham/nyx with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf devanshbatham/nyx
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 devanshbatham/nyx
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use devanshbatham/nyx with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf devanshbatham/nyx
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 "devanshbatham/nyx" \ --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 provenance.json from devanshbatham/nyx: direct link, hf CLI and curl.
- Browser
- Download file 1 kB
-
https://huggingface.co/devanshbatham/nyx/resolve/main/provenance.json
- Command line
-
hf download hf://devanshbatham/nyx/provenance.json
-
curl -L -o provenance.json https://huggingface.co/devanshbatham/nyx/resolve/main/provenance.json
1 kB
| { | |
| "format_version": 1, | |
| "model": "devanshbatham/nyx", | |
| "base_model": "Qwen/Qwen3.5-4B", | |
| "base_revision": "851bf6e806efd8d0a36b00ddf55e13ccb7b8cd0a", | |
| "license": "Apache-2.0", | |
| "artifact": { | |
| "path": "nyx.gguf", | |
| "bytes": 3288582784, | |
| "sha256": "39d64fb19863cfc067e2411fcb2a0444113dda13798b15de5617736d91914359", | |
| "format": "GGUF", | |
| "quantization": "importance-matrix IQ4_XS with selected Q5_K/Q6_K tensors" | |
| }, | |
| "reference": { | |
| "bytes": 8424393056, | |
| "sha256": "b225f62bb79e2f0bc0bcd9fa00dba4579bade89e6b9581537da7fa2482a6b500" | |
| }, | |
| "fidelity_evaluation": { | |
| "cases": 1024, | |
| "reference_correct": 873, | |
| "artifact_correct": 874, | |
| "decision_agreement": 0.9873046875, | |
| "decision_disagreements": 13, | |
| "gains": 7, | |
| "losses": 6 | |
| }, | |
| "tested_runtime": { | |
| "llama_cpp_revision": "e6cef8152f6e8351a870d8e1a98627139c9c379a", | |
| "cpu_load_smoke_test": true, | |
| "full_public_benchmark_on_release_artifact": false, | |
| "nvidia_qualification": false | |
| } | |
| } | |