TurboPilot

TurboPilot is a self-hosted copilot clone which uses the library behind llama.cpp to run the 6 Billion Parameter Salesforce Codegen model in 4GiB of RAM. It is heavily based and inspired by on the fauxpilot project.

NB: This is a proof of concept right now rather than a stable tool. Autocompletion is quite slow in this version of the project. Feel free to play with it, but your mileage may vary.

Getting Started

git clone https://github.com/ravenscroftj/turbopilot
git submodule init
cd ggml
mkdir build
cd build
cmake ..
make codegen codegen-quantize

Getting The Models

Direct Access

You can download the pre-converted, pre-quantized models from Google Drive

Convert The Models Yourself

Start by downloading either the 2B or 6B GPT-J versions of CodeGen.

Convert The Model

python convert-codegen-to-ggml.py ./codegen-6B-multi-gptj 0

Quantize the model

./bin/codegen-quantize ../../codegen-6B-multi-gptj/ggml-model-f32.bin ../../codegen-6B-multi-gptj/ggml-model-quant.bin 2

Run the model

./bin/codegen -t 6 -m ../../codegen-6B-multi-gptj/ggml-model-quant.bin -p "def main("

Acknowledgements

This project would not have been possible without Georgi Gerganov's work on GGML and llama.cpp
It was completely inspired by fauxpilot which I did experiment with for a little while but wanted to try to make the models work without a GPU
The frontend of the project is powered by Venthe's vscode-fauxpilot plugin
The project uses the Salesforce Codegen models.
Thanks to Moyix for his work on converting the Salesforce models to run in a GPT-J architecture. Not only does this confer some speed benefits but it also made it much easier for me to port the models to GGML using the existing gpt-j example code
The model server uses CrowCPP to serve suggestions.

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