Instructions to use Bhargav0044/whisper-small-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bhargav0044/whisper-small-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Bhargav0044/whisper-small-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Bhargav0044/whisper-small-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("Bhargav0044/whisper-small-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46a63f8f2cda468678fa9f4ab9542d42269efff79ae232447418ee24aa25b50c
- Size of remote file:
- 967 MB
- SHA256:
- 0189026d6180fbec894c452a85af092afaaed6f1b0fc2ed46e67f225bb721243
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