Learn how to deploy a Whisper model with diarization and speculative decoding using Hugging Face Inference Endpoints. The implementation of the diarization pipeline is inspired by Insanely Fast Whisper and uses a Pyannote model. Speculative decoding requires the decoder part of the assistant model to have the same architecture as the main model and a batch size of 1. The deployment process involves customizing the pipeline based on your needs, setting up your own endpoint, and passing environment variables to containers hosted on Inference Endpoints.
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