Instructions to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF", filename="ornith-1.0-35b-MTP-graft-down-Q4_0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF 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 petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
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 petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
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 petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
Use Docker
docker model run hf.co/petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
- LM Studio
- Jan
- vLLM
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
- Ollama
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with Ollama:
ollama run hf.co/petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
- Unsloth Studio
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF to start chatting
- Pi
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
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 petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
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 "petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0" \ --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"
- Docker Model Runner
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with Docker Model Runner:
docker model run hf.co/petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
- Lemonade
How to use petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull petr567/Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF:Q4_0
Run and chat with the model
lemonade run user.Ornith-1.0-35B-MTP-Strix-Halo-Hybrid-GGUF-Q4_0
List all available models
lemonade list
| { | |
| "hardware": { | |
| "cpu": "AMD Ryzen AI MAX+ 395", | |
| "gpu": "AMD Radeon 8060S", | |
| "vulkan_arch": "gfx1151", | |
| "memory": "128 GiB UMA" | |
| }, | |
| "baseline": { | |
| "batch_id": "matrix-20260718-093215", | |
| "model": "ornith-1.0-35b-Q4_K_M.gguf", | |
| "requests": 232, | |
| "prompt_tokens": 699947, | |
| "generated_tokens": 68447, | |
| "weighted_decode_tok_s": 61.44647554769253, | |
| "mean_request_decode_tok_s": 65.6805172413793, | |
| "p50_decode_tok_s": 68.45, | |
| "max_decode_tok_s": 75.03, | |
| "wall_seconds": 4362.498008, | |
| "quality_score": 40.833333333333336, | |
| "tasks": 43 | |
| }, | |
| "hybrid": { | |
| "batch_id": "matrix-20260718-152753", | |
| "model": "ornith-1.0-35b-MTP-graft-down-Q4_0.gguf", | |
| "model_sha256": "365a7c02dfd320b9696f189d6dc12bd2b0eabb9f8e58ba9fc8cab3af93c0234b", | |
| "requests": 223, | |
| "prompt_tokens": 668344, | |
| "generated_tokens": 73700, | |
| "weighted_decode_tok_s": 79.66071754591292, | |
| "mean_request_decode_tok_s": 83.94412556053813, | |
| "p50_decode_tok_s": 84.84, | |
| "max_decode_tok_s": 177.48, | |
| "draft_acceptance": 0.658691117006207, | |
| "wall_seconds": 2171.064179, | |
| "quality_score": 40.833333333333336, | |
| "tasks": 43 | |
| }, | |
| "repeated_code_microbenchmark": { | |
| "runs": 5, | |
| "mean_decode_tok_s": 99.087544, | |
| "min_decode_tok_s": 90.367097, | |
| "max_decode_tok_s": 116.945213 | |
| }, | |
| "kv_64k_boundary": { | |
| "prompt_tokens": 62630, | |
| "generated_tokens": 512, | |
| "q8_0": { | |
| "prompt_tok_s": 524.1608964890443, | |
| "decode_tok_s": 70.28649434028986 | |
| }, | |
| "q4_0": { | |
| "prompt_tok_s": 484.7338030491343, | |
| "decode_tok_s": 67.6747740693529 | |
| }, | |
| "decision": "retain q8_0/q8_0" | |
| } | |
| } | |