What is gepard-inference?

Gepard is a text-to-speech system: software that takes written text and turns it into spoken audio. This particular repository is the inference side of the project, meaning the part that actually runs a trained model to generate speech, rather than the part that trains the model in the first place. What makes Gepard notable is that it is built to run on vLLM, a widely used engine for serving large language models efficiently, without needing any specialized code written just for audio generation. It generates a full frame of audio in a single step, which the project says lets a single stream produce speech many times faster than someone speaking it out loud, and lets one graphics card handle many requests from different users at the same time. The system can also clone a voice from a short reference audio clip, so it can speak in a voice you provide it rather than only a stock voice. The project notes voice similarity is slightly reduced when using this optional quality boosting mode. To run it, you need a computer with an NVIDIA graphics card that supports CUDA and Python version 3.12 installed. The project provides simple setup commands that install the needed software into an isolated environment, log you into Hugging Face, a platform used to download the AI model, then start a local server. Once the server is running, you can send it text either through a command line tool or by sending a web request directly, and it returns an audio file back. The project is released under the Apache 2.0 open source license, though the separate audio codec component it depends on at runtime comes from NVIDIA and carries its own, different license terms. Related repositories cover how the underlying model was trained and a separate production ready serving setup.