Whisper Transcription Upgrade for Hugging Face

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Are you utilizing Whisper for transcription? Hold on to your ears! A groundbreaking optimization has emerged: Whisper now incorporates Speaker Diarization, delivering lightning-fast transcription for Hugging Face Inference Endpoints. This innovation introduces an ultra-fast inference system powered by Flash Attention and Speculative Decoding. Leveraging the Custom Handler feature of Hugging Face Inference Endpoints, it achieves unparalleled efficiency, transcribing 60 seconds of audio in just 4.15 seconds using Whisper Large on a single A10G GPU. But that's not all—this implementation combines Whisper with Pyannote's diarization model, enabling precise speaker separation. Moreover, it's fully customizable and adaptable to specific use cases, and it's open-source for seamless deployment. Kudos to Sergei Petrov for this exemplary demonstration of optimizing Generative AI deployments for production with Hugging Face Inference Endpoints. For more details, visit the blog here and access the code here.