Automatic Speech Recognition
Transformers
PyTorch
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use sumet/whisper-tiny-en-US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumet/whisper-tiny-en-US with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sumet/whisper-tiny-en-US")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sumet/whisper-tiny-en-US") model = AutoModelForSpeechSeq2Seq.from_pretrained("sumet/whisper-tiny-en-US") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
862912f | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:efeb7637be88b8c9040ee44ddc00c3e4a17fb282bd89e9cd2d60c73dbebc1d5f
size 4091
|