Instructions to use sanjitaa/small-whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanjitaa/small-whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sanjitaa/small-whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sanjitaa/small-whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("sanjitaa/small-whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- edf4f2650f94f3bf5b459f7db4ea936c9b64bd1291675e1f8dc745ff40c5ac01
- Size of remote file:
- 967 MB
- SHA256:
- b5244d9716720249bf31765c182eae4d5a07ccd00a64adae3b631961e7708ff3
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