Instructions to use mskov/whisper-small-esc50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mskov/whisper-small-esc50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mskov/whisper-small-esc50")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mskov/whisper-small-esc50") model = AutoModelForSpeechSeq2Seq.from_pretrained("mskov/whisper-small-esc50") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bd298e4070769ae0fc8621c355f97eec6881a654ebb199a7c93b5650b239fa8
- Size of remote file:
- 3.77 kB
- SHA256:
- 19b5fefb6501f6a91a47ddbc6573c26ef485f3f9f15c7209a4994e46c6c6e996
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