Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use openai/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-tiny") - Notebooks
- Google Colab
- Kaggle
Correct forced decoder ids
#38
by patrickvonplaten - opened
Any reason why the generation config doesn't match the config here: https://huggingface.co/openai/whisper-tiny/blob/be0ba7c2f24f0127b27863a23a08002af4c2c279/config.json#L26
Config is wrong in this case - the language at index 1 shouldn't be specified in the forced decoder ids. It should be inferred automatically from the audio.
This inconsistency between config and generation config is observed across all Whisper models - I'll open Hub PRs to correct them!