audio-transformers-course

Why we included this project

Moving from text transformers into audio work can be a steep climb, and this free, open-source course is one of the most direct on-ramps for it. The repository holds the full lesson content behind Hugging Face's official Audio Transformers course. It takes architectures you may already know, such as Wav2Vec2, Whisper, and AST, and shows how they apply to real speech and sound work, including automatic speech recognition, audio classification, and text-to-speech. Each chapter pairs explanations with hands-on notebooks that run on the transformers and datasets libraries, so you learn by fine-tuning and evaluating models rather than just reading theory. That makes it useful for self-learners who want structured depth and for teams getting people up to speed on the audio side of the transformers ecosystem. Hugging Face maintains the material and offers it in several languages, which helps it stay reasonably current.