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
Correct long-form generation config parameters 'max_initial_timestamp_index' and 'prev_sot_token_id'.
#32
by patrickvonplaten - opened
Hey openai π,
Your model repository seems to contain outdated generation config parameters, such as 'max_initial_timestamp_index' and is missing the 'prev_sot_token_id' parameter. These parameters need to be updated to correctly handle long-form generation as stated in as part of https://github.com/huggingface/transformers/pull/27658. This PR makes sure that everything is up to date and can be safely merged.
Best, the Transformers team.
patrickvonplaten changed pull request status to merged