FauxPilot
This is an attempt to build a locally hosted alternative to GitHub Copilot. It uses the SalesForce CodeGen models inside of NVIDIA's Triton Inference Server with the FasterTransformer backend.
Prerequisites
You'll need:
- Docker
docker compose>= 1.28- An NVIDIA GPU with Compute Capability >= 6.0 and enough VRAM to run the model you want.
nvidia-dockercurlandzstdfor downloading and unpacking the models.
Note that the VRAM requirements listed by setup.sh are total -- if you have multiple GPUs, you can split the model across them. So, if you have two NVIDIA RTX 3080 GPUs, you should be able to run the 6B model by putting half on each GPU.
Support and Warranty
lmao
Okay, fine, we now have some minimal information on the wiki and a discussion forum where you can ask questions. Still no formal support or warranty though!
Setup
This section describes how to install a Fauxpilot server and clients.
Setting up a FauxPilot Server
Run the setup script to choose a model to use. This will download the model from Huggingface/Moyix in GPT-J format and then convert it for use with FasterTransformer.
Please refer to How to set-up a FauxPilot server.
Client configuration for FauxPilot
We offer some ways to connect to FauxPilot Server. For example, you can create a client by how to open the Openai API, Copilot Plugin, REST API.
Please refer to How to set-up a client.
Terminology
- API: Application Programming Interface
- CC: Compute Capability
- CUDA: Compute Unified Device Architecture
- FT: Faster Transformer
- JSON: JavaScript Object Notation
- gRPC: Remote Procedure call by Google
- GPT-J: A transformer model trained using Ben Wang's Mesh Transformer JAX
- REST: REpresentational State Transfer