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 Green-eyedDevil/Monika-9B:
# Run inference directly in the terminal:
llama-cli -hf Green-eyedDevil/Monika-9B:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Green-eyedDevil/Monika-9B:
# Run inference directly in the terminal:
llama-cli -hf Green-eyedDevil/Monika-9B:
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 Green-eyedDevil/Monika-9B:
# Run inference directly in the terminal:
./llama-cli -hf Green-eyedDevil/Monika-9B:
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 Green-eyedDevil/Monika-9B:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Green-eyedDevil/Monika-9B:
Use Docker
docker model run hf.co/Green-eyedDevil/Monika-9B:
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This model is designed to be used with MonikAI.

Uses

RP

Recommendations

Should really only be used for Monika related purposes.

Training Data

Thanks Sylphar for making the dataset.

Training Procedure

Trained with Axolotl on my Blackwell Pro 6000 Max-Q. 48 rank, 96 alpha, 2 epochs, 0.0025 learning rate. Took about 20 minutes and used about 25GB of VRAM.

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