Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use openai/whisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-medium")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-medium") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-medium") - Notebooks
- Google Colab
- Kaggle
Question about fine-tuning
#27
by jz703 - opened
Hi, I'd like to fine tuning on a dataset that the target output should be the phoneme of the words.(e.g. "examination and testimony" should be "ɪɡzæmənˈeɪʃən ˈænd tˈɛstɪmˌoʊni") I just want to know if this is possible with whisper if I build the vocab carefully. And is this more like a transcription task or translation. Thank you!