Instructions to use Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: llama cli -hf Aliguinga01/rule_violation2:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: llama cli -hf Aliguinga01/rule_violation2:F16
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 Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: ./llama-cli -hf Aliguinga01/rule_violation2:F16
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 Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Aliguinga01/rule_violation2:F16
Use Docker
docker model run hf.co/Aliguinga01/rule_violation2:F16
- LM Studio
- Jan
- Ollama
How to use Aliguinga01/rule_violation2 with Ollama:
ollama run hf.co/Aliguinga01/rule_violation2:F16
- Unsloth Studio
How to use Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Aliguinga01/rule_violation2 to start chatting
- Docker Model Runner
How to use Aliguinga01/rule_violation2 with Docker Model Runner:
docker model run hf.co/Aliguinga01/rule_violation2:F16
- Lemonade
How to use Aliguinga01/rule_violation2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Aliguinga01/rule_violation2:F16
Run and chat with the model
lemonade run user.rule_violation2-F16
List all available models
lemonade list
- Atomic Chat
| set -e | |
| # Parse command line arguments | |
| CONVERTED_MODEL="" | |
| PROMPTS_FILE="" | |
| USE_POOLING="" | |
| while [[ $# -gt 0 ]]; do | |
| case $1 in | |
| -p|--prompts-file) | |
| PROMPTS_FILE="$2" | |
| shift 2 | |
| ;; | |
| --pooling) | |
| USE_POOLING="1" | |
| shift | |
| ;; | |
| *) | |
| if [ -z "$CONVERTED_MODEL" ]; then | |
| CONVERTED_MODEL="$1" | |
| fi | |
| shift | |
| ;; | |
| esac | |
| done | |
| # First try command line argument, then environment variable | |
| CONVERTED_MODEL="${CONVERTED_MODEL:-"$CONVERTED_EMBEDDING_MODEL"}" | |
| # Final check if we have a model path | |
| if [ -z "$CONVERTED_MODEL" ]; then | |
| echo "Error: Model path must be provided either as:" >&2 | |
| echo " 1. Command line argument" >&2 | |
| echo " 2. CONVERTED_EMBEDDING_MODEL environment variable" >&2 | |
| exit 1 | |
| fi | |
| # Read prompt from file or use default | |
| if [ -n "$PROMPTS_FILE" ]; then | |
| if [ ! -f "$PROMPTS_FILE" ]; then | |
| echo "Error: Prompts file '$PROMPTS_FILE' not found" >&2 | |
| exit 1 | |
| fi | |
| PROMPT=$(cat "$PROMPTS_FILE") | |
| else | |
| PROMPT="Hello world today" | |
| fi | |
| echo $CONVERTED_MODEL | |
| cmake --build ../../build --target llama-logits -j8 | |
| # TODO: update logits.cpp to accept a --file/-f option for the prompt | |
| if [ -n "$USE_POOLING" ]; then | |
| ../../build/bin/llama-logits -m "$CONVERTED_MODEL" -embd-mode -pooling "$PROMPT" | |
| else | |
| ../../build/bin/llama-logits -m "$CONVERTED_MODEL" -embd-mode "$PROMPT" | |
| fi | |