How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf superdrew100/UwU_phi3_mini:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf superdrew100/UwU_phi3_mini:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf superdrew100/UwU_phi3_mini:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf superdrew100/UwU_phi3_mini:Q4_K_M
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 superdrew100/UwU_phi3_mini:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf superdrew100/UwU_phi3_mini:Q4_K_M
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 superdrew100/UwU_phi3_mini:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf superdrew100/UwU_phi3_mini:Q4_K_M
Use Docker
docker model run hf.co/superdrew100/UwU_phi3_mini:Q4_K_M
Quick Links

UwU_phi3_mini-unsloth_V1.Q4_K_M.gguf

-is trained on only 20% for one epoch of the

https://huggingface.co/datasets/superdrew100/UwU_Alpaca_data_V2

Downloads last month
34
GGUF
Model size
4B params
Architecture
llama
Hardware compatibility
Log In to add your hardware

4-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support