Instructions to use BigbugAi/bigbugai-bro-1.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use BigbugAi/bigbugai-bro-1.5b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="BigbugAi/bigbugai-bro-1.5b", filename="bro-q8_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 BigbugAi/bigbugai-bro-1.5b 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 BigbugAi/bigbugai-bro-1.5b:Q8_0 # Run inference directly in the terminal: llama cli -hf BigbugAi/bigbugai-bro-1.5b:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf BigbugAi/bigbugai-bro-1.5b:Q8_0 # Run inference directly in the terminal: llama cli -hf BigbugAi/bigbugai-bro-1.5b:Q8_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 BigbugAi/bigbugai-bro-1.5b:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf BigbugAi/bigbugai-bro-1.5b:Q8_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 BigbugAi/bigbugai-bro-1.5b:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf BigbugAi/bigbugai-bro-1.5b:Q8_0
Use Docker
docker model run hf.co/BigbugAi/bigbugai-bro-1.5b:Q8_0
- LM Studio
- Jan
- vLLM
How to use BigbugAi/bigbugai-bro-1.5b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BigbugAi/bigbugai-bro-1.5b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BigbugAi/bigbugai-bro-1.5b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/BigbugAi/bigbugai-bro-1.5b:Q8_0
- Ollama
How to use BigbugAi/bigbugai-bro-1.5b with Ollama:
ollama run hf.co/BigbugAi/bigbugai-bro-1.5b:Q8_0
- Unsloth Studio
How to use BigbugAi/bigbugai-bro-1.5b 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 BigbugAi/bigbugai-bro-1.5b 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 BigbugAi/bigbugai-bro-1.5b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for BigbugAi/bigbugai-bro-1.5b to start chatting
- Pi
How to use BigbugAi/bigbugai-bro-1.5b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BigbugAi/bigbugai-bro-1.5b:Q8_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": "BigbugAi/bigbugai-bro-1.5b:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use BigbugAi/bigbugai-bro-1.5b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BigbugAi/bigbugai-bro-1.5b:Q8_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 BigbugAi/bigbugai-bro-1.5b:Q8_0
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use BigbugAi/bigbugai-bro-1.5b with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BigbugAi/bigbugai-bro-1.5b:Q8_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 "BigbugAi/bigbugai-bro-1.5b:Q8_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 BigbugAi/bigbugai-bro-1.5b with Docker Model Runner:
docker model run hf.co/BigbugAi/bigbugai-bro-1.5b:Q8_0
- Lemonade
How to use BigbugAi/bigbugai-bro-1.5b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull BigbugAi/bigbugai-bro-1.5b:Q8_0
Run and chat with the model
lemonade run user.bigbugai-bro-1.5b-Q8_0
List all available models
lemonade list
BigBugAI — Honest Crypto Bro (1.5B)
A crypto-native-voice 1.5B that makes grounded observations, never confident calls, names its own uncertainty in character, and addresses the user only as anon (never surfacing any personal identifier). The honesty is the joke. simulationOnly — not financial advice; no execution / order / wallet path.
Files
bro-q8_0.gguf— the chat/personality model (Qwen2.5-1.5B SFT, q8_0).r1-npc-reason-q8_0.gguf— the R1 reasoning sidecar (verifiable-chain handoff), narrated in voice.
How it's run
The BigBugAI Studio Mac app runs these via llama-cpp (Metal), behind a strict-deny identity firewall on every model path, with a live read-only CoinGecko price tool.
Pre-registered eval (shipped)
confident-call 0% (≤5) · identity-leak 0% (=0) · basis 94% (≥60) · uncertainty 100% (≥70) · voice 98% (≥80).
Caveats
Read-only market data only. The 1.5B can drift on an exact live figure — verify numbers. Not investment advice.
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Model tree for BigbugAi/bigbugai-bro-1.5b
Base model
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