Instructions to use BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6", filename="BugTraceAI-CORE-Ultra-SFT-Q6_K.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 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 BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K # Run inference directly in the terminal: llama cli -hf BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K # Run inference directly in the terminal: llama cli -hf BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
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 BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K # Run inference directly in the terminal: ./llama-cli -hf BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
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 BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
Use Docker
docker model run hf.co/BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
- LM Studio
- Jan
- Ollama
How to use BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 with Ollama:
ollama run hf.co/BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
- Unsloth Studio
How to use BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 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 BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 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 BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 to start chatting
- Pi
How to use BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
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": "BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
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 BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
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 "BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K" \ --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 BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 with Docker Model Runner:
docker model run hf.co/BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
- Lemonade
How to use BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull BugTraceAI/BugTraceAI-CORE-Ultra-27B-Q6:Q6_K
Run and chat with the model
lemonade run user.BugTraceAI-CORE-Ultra-27B-Q6-Q6_K
List all available models
lemonade list
BF16/Q8_0 GGUF?
Could you release the BF16 or Q8_0 GGUF files? I have a DGX Spark and it would fit easily, likely with better output quality.
Hey mrexodia! Great to hear you have a DGX Spark β that's serious hardware π₯ The BF16 safetensors base model is ~54GB and Q8_0 GGUF would be ~29GB. We didn't include them initially due to storage constraints on our end, but this is definitely on our radar given the community interest. If there's enough demand we'll prioritize it. You could also self-quantize from the base Qwen2.5-27B + our LoRA adapter in apex_final/ to get a BF16 merged version.