Usage of huggingface for OpenAI whisper
Hello, I need to fine tune a whisper model. When I looked for forums or etc. they are keep telling that I should use Hugginface to create an audio file. Do I have to use it firstly ? Secondly, for openai/whisper are we using huggingface in the background ? What is the benefits of it ? If I don’t want to use it can I use opeanAI/whisper ?
2024-02-05T19:41:15Z
Hi,OpenAI initially open-sourced Whisper atGitHub - openai/whisper: Robust Speech Recognition via Large-Scale Weak Supervision. This is only a PyTorch implementation, unrelated to Hugging Face. It is meant for inference-only.Hugging Face hasimplementedWhisper in the Transformers library, with various additional features, most notablyability to fine-tune on custom data:Fine-Tune Whisper For Multilingual ASR with 🤗 Transformersability to speed up transcription massively:GitHub - Vaibhavs10/insanely-fast-whisperoptimize it for production deployment:https://twitter.com/IlysMoutawwakil/status/1667258837194383360distil Whisper into a smaller student model that is equivalent in terms of performance:GitHub - huggingface/distil-whisper: Distilled variant of Whisper for speech recognition. 6x faster, 50% smaller, within 1% word error rate.etc.