Instructions to use CISCai/gorilla-openfunctions-v2-SOTA-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use CISCai/gorilla-openfunctions-v2-SOTA-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="CISCai/gorilla-openfunctions-v2-SOTA-GGUF", filename="gorilla-openfunctions-v2.IQ1_S.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 CISCai/gorilla-openfunctions-v2-SOTA-GGUF 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 CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S # Run inference directly in the terminal: llama cli -hf CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S # Run inference directly in the terminal: llama cli -hf CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
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 CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S # Run inference directly in the terminal: ./llama-cli -hf CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
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 CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
Use Docker
docker model run hf.co/CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
- LM Studio
- Jan
- vLLM
How to use CISCai/gorilla-openfunctions-v2-SOTA-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CISCai/gorilla-openfunctions-v2-SOTA-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CISCai/gorilla-openfunctions-v2-SOTA-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
- Ollama
How to use CISCai/gorilla-openfunctions-v2-SOTA-GGUF with Ollama:
ollama run hf.co/CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
- Unsloth Studio
How to use CISCai/gorilla-openfunctions-v2-SOTA-GGUF 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 CISCai/gorilla-openfunctions-v2-SOTA-GGUF 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 CISCai/gorilla-openfunctions-v2-SOTA-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for CISCai/gorilla-openfunctions-v2-SOTA-GGUF to start chatting
- Pi
How to use CISCai/gorilla-openfunctions-v2-SOTA-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
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": "CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use CISCai/gorilla-openfunctions-v2-SOTA-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
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 CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use CISCai/gorilla-openfunctions-v2-SOTA-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
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 "CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S" \ --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 CISCai/gorilla-openfunctions-v2-SOTA-GGUF with Docker Model Runner:
docker model run hf.co/CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
- Lemonade
How to use CISCai/gorilla-openfunctions-v2-SOTA-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull CISCai/gorilla-openfunctions-v2-SOTA-GGUF:IQ1_S
Run and chat with the model
lemonade run user.gorilla-openfunctions-v2-SOTA-GGUF-IQ1_S
List all available models
lemonade list
importance matrix
Do you mind sharing how you generated the importance matrix?
also, how did you overcome this: https://huggingface.co/gorilla-llm/gorilla-openfunctions-v2/discussions/2
@sanjay920 Normally I would extract data relevant for the input/output of the model and generate a text file, however in this case since the model is mostly ingesting JSON anyway I used the file (linked in the README.md) as-is and it turned out to work very well. :) Then it is simply a case of running the following command:
./imatrix -m gorilla-openfunctions-v2.fp16.gguf -f gorilla_openfunctions_v1_train.json -o gorilla-openfunctions-v2.imatrix.dat -ngl 99 -c 4096 --chunks 256
I created a new chat_template as seen in PR #4 to fix the issues with the original one.
awesome! thanks for the info :)