Instructions to use peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B 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 peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B 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 peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S # Run inference directly in the terminal: llama cli -hf peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S # Run inference directly in the terminal: llama cli -hf peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
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 peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
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 peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
Use Docker
docker model run hf.co/peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
- LM Studio
- Jan
- vLLM
How to use peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
- Ollama
How to use peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B with Ollama:
ollama run hf.co/peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
- Unsloth Desktop
- Pi
How to use peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
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": "peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B with Docker Model Runner:
docker model run hf.co/peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
- Lemonade
How to use peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
Run and chat with the model
lemonade run user.Unsloth-Ornith-1.5-35B-A3B-UD-Q4_K_S
List all available models
lemonade list
- Hermes Agent
How to use peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
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 peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S
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 "peculiar-ragdoll/Unsloth-Ornith-1.5-35B-A3B:UD-Q4_K_S" \ --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"
Unsloth + No broken MTP
While everybody is racing to just make some GGUFs, you're the only one who noticed the broken MTPs and removed the useless weight. Also a fan of your sharp template for other Qwen models. Have you tested the sharp template with this?
Thank you very much.
Thanks! :) Yes I've tested the sharp template with Ornith 1.5 and I'm benching it now, will be releasing the benchmarks when I make a repo for the sharpened and dynamically quantized ornith 1.5, it's looking really promising!
i wish someone would replace the mtp on this model with a working one. the speed is already very good. with mtp it would slap
Agreed! Btw the Sharp UnslothOrnith with the coding-weighted imatrix is now up with benchmarks as TielCoder: https://huggingface.co/peculiar-ragdoll/Tiel-Coder-35B-A3B-GGUF
This build absolutely destroys with the Sharp template! :)
Ornith-ai has now shipped a fixed MTP for Ornith-1.5:
https://huggingface.co/ornith-ai/Ornith-1.5-35B-A3B/discussions/21#6a8bcde1aadd12a8526ce71b
Thanks for the heads up!
FYI, TielCoder (the Sharp UnslothOrnith-1.5) now has the MTP head too! https://huggingface.co/peculiar-ragdoll/Tiel-Coder-35B-A3B-GGUF-MTP
@peculiar-ragdoll what about kat-coder-v2.5? Isn't it better than ornith for coding? After your finetunes should be even better.
Thanks for the question! KAT actually became worse when I tried to improve it hahah :) so I ditched it. And Tiel beats KAT on my benchmarks
Good to know. Thanks!
Hello! Will u update the MTP?