Instructions to use Sculptor-AI/Ursa_Minor_Smashed 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 Sculptor-AI/Ursa_Minor_Smashed 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 Sculptor-AI/Ursa_Minor_Smashed:F32 # Run inference directly in the terminal: llama cli -hf Sculptor-AI/Ursa_Minor_Smashed:F32
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Sculptor-AI/Ursa_Minor_Smashed:F32 # Run inference directly in the terminal: llama cli -hf Sculptor-AI/Ursa_Minor_Smashed:F32
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 Sculptor-AI/Ursa_Minor_Smashed:F32 # Run inference directly in the terminal: ./llama-cli -hf Sculptor-AI/Ursa_Minor_Smashed:F32
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 Sculptor-AI/Ursa_Minor_Smashed:F32 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Sculptor-AI/Ursa_Minor_Smashed:F32
Use Docker
docker model run hf.co/Sculptor-AI/Ursa_Minor_Smashed:F32
- Llama new
- LM Studio
- Jan
- Ollama
How to use Sculptor-AI/Ursa_Minor_Smashed with Ollama:
ollama run hf.co/Sculptor-AI/Ursa_Minor_Smashed:F32
- Unsloth Desktop
- Docker Model Runner
How to use Sculptor-AI/Ursa_Minor_Smashed with Docker Model Runner:
docker model run hf.co/Sculptor-AI/Ursa_Minor_Smashed:F32
- Lemonade
How to use Sculptor-AI/Ursa_Minor_Smashed with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Sculptor-AI/Ursa_Minor_Smashed:F32
Run and chat with the model
lemonade run user.Ursa_Minor_Smashed-F32
List all available models
lemonade list
- Atomic Chat
Download setup-cuda.sh from Sculptor-AI/Ursa_Minor_Smashed: direct link, hf CLI and curl.
- Browser
- Download file 3.26 kB
-
https://huggingface.co/Sculptor-AI/Ursa_Minor_Smashed/resolve/main/setup-cuda.sh
- Command line
-
hf download hf://Sculptor-AI/Ursa_Minor_Smashed/setup-cuda.sh
-
curl -L -o setup-cuda.sh https://huggingface.co/Sculptor-AI/Ursa_Minor_Smashed/resolve/main/setup-cuda.sh
3.26 kB
| # CUDA Setup script for Ursa Minor Smashed model | |
| echo "π₯ Setting up CUDA environment for Ursa Minor Smashed model..." | |
| # Check if NVIDIA GPU is available | |
| if ! command -v nvidia-smi &> /dev/null; then | |
| echo "β ERROR: nvidia-smi not found. Make sure NVIDIA drivers are installed." | |
| exit 1 | |
| fi | |
| echo "π Checking GPU information..." | |
| nvidia-smi | |
| # Check CUDA version | |
| CUDA_VERSION=$(nvidia-smi | grep "CUDA Version" | awk '{print $9}' | cut -d. -f1,2) | |
| echo "π Detected CUDA Version: $CUDA_VERSION" | |
| # Create virtual environment | |
| echo "π¦ Creating virtual environment..." | |
| python -m venv venv-cuda | |
| # Activate virtual environment | |
| if [[ "$OSTYPE" == "msys" || "$OSTYPE" == "win32" ]]; then | |
| source venv-cuda/Scripts/activate | |
| else | |
| source venv-cuda/bin/activate | |
| fi | |
| echo "β Virtual environment activated" | |
| # Upgrade pip | |
| pip install --upgrade pip | |
| # Install CUDA requirements | |
| echo "π Installing CUDA requirements..." | |
| echo "This may take a few minutes as PyTorch CUDA packages are large..." | |
| # Detect CUDA version and install appropriate PyTorch | |
| if [[ "$CUDA_VERSION" == "12."* ]]; then | |
| echo "Installing PyTorch for CUDA 12.1..." | |
| pip install torch torchaudio torchvision --extra-index-url https://download.pytorch.org/whl/cu121 | |
| elif [[ "$CUDA_VERSION" == "11."* ]]; then | |
| echo "Installing PyTorch for CUDA 11.8..." | |
| pip install torch torchaudio torchvision --extra-index-url https://download.pytorch.org/whl/cu118 | |
| else | |
| echo "β οΈ Warning: Unsupported CUDA version $CUDA_VERSION" | |
| echo "Installing default CUDA 11.8 PyTorch..." | |
| pip install torch torchaudio torchvision --extra-index-url https://download.pytorch.org/whl/cu118 | |
| fi | |
| # Install remaining requirements | |
| echo "π Installing remaining dependencies..." | |
| pip install -r requirements-cuda.txt | |
| # Test CUDA availability | |
| echo "π§ͺ Testing CUDA setup..." | |
| python -c " | |
| import torch | |
| print(f'PyTorch version: {torch.__version__}') | |
| print(f'CUDA available: {torch.cuda.is_available()}') | |
| if torch.cuda.is_available(): | |
| print(f'CUDA device count: {torch.cuda.device_count()}') | |
| print(f'Current CUDA device: {torch.cuda.current_device()}') | |
| print(f'CUDA device name: {torch.cuda.get_device_name()}') | |
| print(f'CUDA version: {torch.version.cuda}') | |
| else: | |
| print('β CUDA not available in PyTorch installation') | |
| exit(1) | |
| " | |
| # Verify model file exists | |
| if [[ -f "model_optimized.pt" ]]; then | |
| echo "β Model file found: model_optimized.pt" | |
| else | |
| echo "β οΈ Warning: model_optimized.pt not found in current directory" | |
| echo "Make sure you have the model file in the same directory as this script" | |
| fi | |
| echo "" | |
| echo "π CUDA setup complete!" | |
| echo "" | |
| echo "π Usage Instructions:" | |
| echo "To activate CUDA environment:" | |
| if [[ "$OSTYPE" == "msys" || "$OSTYPE" == "win32" ]]; then | |
| echo " source venv-cuda/Scripts/activate" | |
| else | |
| echo " source venv-cuda/bin/activate" | |
| fi | |
| echo "" | |
| echo "To run CUDA inference:" | |
| echo " python inference_cuda.py --prompt 'Your prompt here'" | |
| echo "" | |
| echo "To run CUDA chat:" | |
| echo " python chat_cuda.py" | |
| echo "" | |
| echo "To run CUDA benchmark:" | |
| echo " python benchmark_cuda.py" | |
| echo "" | |
| echo "π Test your setup:" | |
| echo " python -c \"import torch; print('CUDA available:', torch.cuda.is_available())\"" |