Instructions to use badtheorylabs/BTL-3-Compact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use badtheorylabs/BTL-3-Compact with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="badtheorylabs/BTL-3-Compact", filename="model/BTL-3-Compact-AVQ2.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 badtheorylabs/BTL-3-Compact 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 badtheorylabs/BTL-3-Compact # Run inference directly in the terminal: llama cli -hf badtheorylabs/BTL-3-Compact
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf badtheorylabs/BTL-3-Compact # Run inference directly in the terminal: llama cli -hf badtheorylabs/BTL-3-Compact
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 badtheorylabs/BTL-3-Compact # Run inference directly in the terminal: ./llama-cli -hf badtheorylabs/BTL-3-Compact
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 badtheorylabs/BTL-3-Compact # Run inference directly in the terminal: ./build/bin/llama-cli -hf badtheorylabs/BTL-3-Compact
Use Docker
docker model run hf.co/badtheorylabs/BTL-3-Compact
- LM Studio
- Jan
- vLLM
How to use badtheorylabs/BTL-3-Compact with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "badtheorylabs/BTL-3-Compact" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "badtheorylabs/BTL-3-Compact", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/badtheorylabs/BTL-3-Compact
- Ollama
How to use badtheorylabs/BTL-3-Compact with Ollama:
ollama run hf.co/badtheorylabs/BTL-3-Compact
- Unsloth Studio
How to use badtheorylabs/BTL-3-Compact 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 badtheorylabs/BTL-3-Compact 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 badtheorylabs/BTL-3-Compact to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for badtheorylabs/BTL-3-Compact to start chatting
- Pi
How to use badtheorylabs/BTL-3-Compact with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf badtheorylabs/BTL-3-Compact
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": "badtheorylabs/BTL-3-Compact" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use badtheorylabs/BTL-3-Compact with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf badtheorylabs/BTL-3-Compact
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 badtheorylabs/BTL-3-Compact
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use badtheorylabs/BTL-3-Compact with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf badtheorylabs/BTL-3-Compact
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 "badtheorylabs/BTL-3-Compact" \ --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 badtheorylabs/BTL-3-Compact with Docker Model Runner:
docker model run hf.co/badtheorylabs/BTL-3-Compact
- Lemonade
How to use badtheorylabs/BTL-3-Compact with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull badtheorylabs/BTL-3-Compact
Run and chat with the model
lemonade run user.BTL-3-Compact-{{QUANT_TAG}}List all available models
lemonade list
Thinking too much
Any fix for the infinite thinking?
rolling out a fix today. im very sorry about that
done, check updates
before anything else, congrats for the project. really nice initiative.
unfortunately, for me, I need thinking mode, so this fix will not help me.
it should the first fix was implemented as an emergency we fixed the thinking problem completely. id update the model readme now.
im sorry about this