Powerful ASR + diarization + speculative decoding with Hugging Face Inference Endpoints

What changed

We'll solve this challenge using a custom inference handler, which will implement the Automatic Speech Recognition (ASR) and Diarization pipeline on Inference Endpoints, as well as supporting speculative decoding. The implementation of the diarization pipeline is inspired by the famous Insanely Fast Whisper, and it uses a Pyannote model for diarization. This will also be a demonstration of how flexible Inference Endpoints are and that you can host pretty much anything there.

Why it matters

A concrete addition to Practical AI: Tools, Models & Frameworks: it changes what's available to builders today rather than being general commentary.

How it compares

Related prior coverage to compare against:

• Speculative Decoding for 2x Faster Whisper Inference
• Deploy LLMs with Hugging Face Inference Endpoints
• Remote VAEs for decoding with Inference Endpoints 🤗

• Speculative Decoding for 2x Faster Whisper Inference similarity 0.43
• Deploy LLMs with Hugging Face Inference Endpoints similarity 0.40
• Remote VAEs for decoding with Inference Endpoints 🤗 similarity 0.38