Instructions to use microsoft/Phi-3-mini-4k-instruct-gguf 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 microsoft/Phi-3-mini-4k-instruct-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 microsoft/Phi-3-mini-4k-instruct-gguf # Run inference directly in the terminal: llama cli -hf microsoft/Phi-3-mini-4k-instruct-gguf
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf microsoft/Phi-3-mini-4k-instruct-gguf # Run inference directly in the terminal: llama cli -hf microsoft/Phi-3-mini-4k-instruct-gguf
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 microsoft/Phi-3-mini-4k-instruct-gguf # Run inference directly in the terminal: ./llama-cli -hf microsoft/Phi-3-mini-4k-instruct-gguf
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 microsoft/Phi-3-mini-4k-instruct-gguf # Run inference directly in the terminal: ./build/bin/llama-cli -hf microsoft/Phi-3-mini-4k-instruct-gguf
Use Docker
docker model run hf.co/microsoft/Phi-3-mini-4k-instruct-gguf
- LM Studio
- Jan
- vLLM
How to use microsoft/Phi-3-mini-4k-instruct-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "microsoft/Phi-3-mini-4k-instruct-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": "microsoft/Phi-3-mini-4k-instruct-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/microsoft/Phi-3-mini-4k-instruct-gguf
- Ollama
How to use microsoft/Phi-3-mini-4k-instruct-gguf with Ollama:
ollama run hf.co/microsoft/Phi-3-mini-4k-instruct-gguf
- Unsloth Studio
How to use microsoft/Phi-3-mini-4k-instruct-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 microsoft/Phi-3-mini-4k-instruct-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 microsoft/Phi-3-mini-4k-instruct-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for microsoft/Phi-3-mini-4k-instruct-gguf to start chatting
- Docker Model Runner
How to use microsoft/Phi-3-mini-4k-instruct-gguf with Docker Model Runner:
docker model run hf.co/microsoft/Phi-3-mini-4k-instruct-gguf
- Lemonade
How to use microsoft/Phi-3-mini-4k-instruct-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull microsoft/Phi-3-mini-4k-instruct-gguf
Run and chat with the model
lemonade run user.Phi-3-mini-4k-instruct-gguf-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Can't reproduce
How were the gguf versions made? Given that Phi3ForCausalLM is not yet supported by llama.cpp
Architecture 'Phi3ForCausalLM' not supported
You can use convert-hf-to-gguf.py from llama.cpp and then just quantize it the way you want.
I am able to create a custom fine-tune and convert it to gguf file via the convert-hf-to-gguf.py.
But not able to quantize it .... llama.cpp returns llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'phi3'
I am on the latest llama.cpp commit, which should include the phi3 architecture.
Can you please push me in the right direction how to solve it?
How about:
Save the safetensors and configs in models subdirectory
./convert-hf-to-gguf.py models/Phi-3
./quantize models/Phi-3/ggml-model-f16.gguf models/Phi-3/Phi-3-model-Q4_K_M.gguf Q4_K_M
It works but the issue was somewhere else. I was not using the right quantize script.
I rebuilt llama.cpp from source via make and it works!
llama_model_quantize_internal: model size = 7288.51 MB
llama_model_quantize_internal: quant size = 2281.66 MB
Please ensure that you are using a llama.cpp build later than 2717, which has support for Phi-3.