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
9e3a41c | 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 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 | [CmdletBinding()]
param(
[Parameter()]
[string]$ModelDir = 'C:\Models\Ornith-MTP',
[Parameter()]
[ValidateRange(1, 65535)]
[int]$Port = 18081,
[Parameter()]
[ValidateRange(4096, 131072)]
[int]$Context = 16384,
[Parameter()]
[string]$ContainerName = 'ornith-mtp-api'
)
$ErrorActionPreference = 'Stop'
$Image = 'ghcr.io/ggml-org/llama.cpp@sha256:1b3d1458ccda7287feab41b8001311acc03e24cde99ec0a2908fe83830562f38'
$ModelFile = 'ornith-1.0-35b-MTP-graft-down-Q4_0.gguf'
$ModelPath = Join-Path $ModelDir $ModelFile
if (-not (Get-Command docker -ErrorAction SilentlyContinue)) {
throw 'docker.exe was not found. Install and start Docker Desktop first.'
}
if (-not (Test-Path -LiteralPath $ModelPath -PathType Leaf)) {
throw "Model file was not found: $ModelPath"
}
$existing = docker ps -a --filter "name=^/${ContainerName}$" --format '{{.Names}}'
if ($LASTEXITCODE -ne 0) {
throw 'Docker is unavailable. Start Docker Desktop and verify WSL2/NVIDIA support.'
}
if ($existing -contains $ContainerName) {
throw "Container '$ContainerName' already exists. Stop it with: docker stop $ContainerName"
}
Write-Host "Starting $ContainerName on http://127.0.0.1:$Port ..."
$DockerArgs = @(
'run', '--detach', '--rm',
'--name', $ContainerName,
'--gpus', 'all',
'--publish', "127.0.0.1:${Port}:8080",
'--mount', "type=bind,source=$ModelDir,target=/models,readonly",
$Image,
'--model', "/models/$ModelFile",
'--alias', 'ornith-1.0-35b-mtp',
'--host', '0.0.0.0',
'--port', '8080',
'--ctx-size', [string]$Context,
'--parallel', '1',
'--n-gpu-layers', 'all',
'--cpu-moe',
'--no-mmap',
'--batch-size', '2048',
'--ubatch-size', '512',
'--flash-attn', 'on',
'--cache-type-k', 'q8_0',
'--cache-type-v', 'q8_0',
'--jinja',
'--metrics',
'--spec-type', 'ngram-mod,draft-mtp',
'--spec-draft-n-max', '2',
'--spec-draft-n-min', '1',
'--spec-draft-p-min', '0.20',
'--spec-ngram-mod-n-min', '48',
'--spec-ngram-mod-n-max', '64',
'--spec-ngram-mod-n-match', '24'
)
$ContainerId = & docker @DockerArgs
if ($LASTEXITCODE -ne 0) {
throw 'docker run failed. Review the Docker Desktop and NVIDIA configuration.'
}
Write-Host "Container: $ContainerId"
$HealthUrl = "http://127.0.0.1:$Port/health"
$Deadline = (Get-Date).AddMinutes(5)
do {
Start-Sleep -Seconds 2
try {
$Health = Invoke-RestMethod -Uri $HealthUrl -TimeoutSec 5
if ($Health.status -eq 'ok') {
Write-Host 'Ornith endpoint is ready.' -ForegroundColor Green
Write-Host "OpenAI base URL: http://127.0.0.1:$Port/v1"
Write-Host 'Model: ornith-1.0-35b-mtp'
Write-Host "Logs: docker logs -f $ContainerName"
Write-Host "Stop: docker stop $ContainerName"
exit 0
}
} catch {
# Model loading is still in progress.
}
} while ((Get-Date) -lt $Deadline)
Write-Warning "Endpoint did not become ready within five minutes. Inspect: docker logs $ContainerName"
exit 1
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