Instructions to use senthilsdglakhsg/phi3-Q4.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 senthilsdglakhsg/phi3-Q4.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 senthilsdglakhsg/phi3-Q4.gguf # Run inference directly in the terminal: llama cli -hf senthilsdglakhsg/phi3-Q4.gguf
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf senthilsdglakhsg/phi3-Q4.gguf # Run inference directly in the terminal: llama cli -hf senthilsdglakhsg/phi3-Q4.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 senthilsdglakhsg/phi3-Q4.gguf # Run inference directly in the terminal: ./llama-cli -hf senthilsdglakhsg/phi3-Q4.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 senthilsdglakhsg/phi3-Q4.gguf # Run inference directly in the terminal: ./build/bin/llama-cli -hf senthilsdglakhsg/phi3-Q4.gguf
Use Docker
docker model run hf.co/senthilsdglakhsg/phi3-Q4.gguf
- LM Studio
- Jan
- vLLM
How to use senthilsdglakhsg/phi3-Q4.gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "senthilsdglakhsg/phi3-Q4.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": "senthilsdglakhsg/phi3-Q4.gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/senthilsdglakhsg/phi3-Q4.gguf
- Ollama
How to use senthilsdglakhsg/phi3-Q4.gguf with Ollama:
ollama run hf.co/senthilsdglakhsg/phi3-Q4.gguf
- Unsloth Desktop
- Docker Model Runner
How to use senthilsdglakhsg/phi3-Q4.gguf with Docker Model Runner:
docker model run hf.co/senthilsdglakhsg/phi3-Q4.gguf
- Lemonade
How to use senthilsdglakhsg/phi3-Q4.gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull senthilsdglakhsg/phi3-Q4.gguf
Run and chat with the model
lemonade run user.phi3-Q4.gguf-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Phi-3 Mini (GGUF Quantized - Q4_K_M)
Model Description
This repository contains a quantized GGUF version of the Phi-3 Mini 128K Instruct model.
- Base Model: microsoft/Phi-3-mini-128k-instruct
- Format: GGUF
- Quantization: Q4_K_M
- Framework: llama.cpp
This model is optimized for efficient local inference with reduced memory usage.
Intended Use
- Local LLM inference
- Chatbots
- Lightweight deployments
- CPU/GPU inference using llama.cpp
Model Details
Base Model
- Microsoft Phi-3 Mini (128K context)
Conversion
- Converted from Hugging Face format โ GGUF
Quantization
- Method: Q4_K_M
- Tool: llama.cpp quantize
This reduces model size while maintaining reasonable performance.
How to Use
Using llama.cpp
./llama-cli -m model-q4.gguf -p "Explain AI simply"
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Hardware compatibility
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