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

chatpsy-gpt : GGUF

This model was finetuned and converted to GGUF format using Unsloth.

Example usage:

  • For text only LLMs: ./llama.cpp/llama-cli -hf halilbabacan/chatpsy-gpt --jinja
  • For multimodal models: ./llama.cpp/llama-mtmd-cli -hf halilbabacan/chatpsy-gpt --jinja

Available Model files:

  • gpt-oss-20b.MXFP4.gguf

Ollama

An Ollama Modelfile is included for easy deployment. This was trained 2x faster with Unsloth

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GGUF
Model size
21B params
Architecture
gpt-oss
Hardware compatibility
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