feat: added example FastAPI-based inference server for Qwen-ASR

[kyr0]

Addressing #15 and a few other questions, I've implemented, tested and benchmarked Qwen-ASR on a 1x NVIDIA H200 NVL throughly, coming up with this inference server implementation that is both simple and fully-featured. This might serve as a boilerplate for more decent implementations -- I believe this is quite a good sweet-spot right now. It does scale well under load, it is configurable, yet still easy to understand. I've also implemented readiness and simple monitoring/SRE features. Forced Aligner is supported as well -- every feature documented in the examples folder should be addressable with this easily. Also, the server.py is volume mounted; so you don't need to rebuild the container on app code change -- another DX improvement. The container also loads the model in HF_HOME of the host. Last but not least, I've provided local and remote reference audios that were generated with ... Qwen-TTS :)

I hope this will reduce the load of issues opened because of confusion.

Requirements: NVIDIA Container Toolkit should be installed on the host (!).

[RomiVu]

AI-generated garbage

[kyr0]

@RomiVu Have you even tried it? You have 2 contributions this year and you react like this on a working solution that has already gathered a few stars? I really wonder how bitter you must feel.. https://github.com/kyr0/fast-qwen-asr-inference-vllm