Speculative Decoding for 2x Faster Whisper Inference

What changed

While the transcription accuracy is exceptional, the inference time is very slow. A 1 hour audio clip takes upwards of 6 minutes to transcribe on a 16GB T4 GPU, even after leveraging inference optimisations like flash attention, half-precision, and chunking. Let's load the weights for our new assistant model, Whisper tiny.

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:

• Powerful ASR + diarization + speculative decoding with Hugging Face Inference Endpoints
• Introducing Whisper
• Make LLM Fine-tuning 2x faster with Unsloth and 🤗 TRL

• Powerful ASR + diarization + speculative decoding with Hugging Face Inference Endpoints similarity 0.43
• Introducing Whisper similarity 0.39
• Make LLM Fine-tuning 2x faster with Unsloth and 🤗 TRL similarity 0.30