Instructions to use h9LtLSb/whisper-small-uk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use h9LtLSb/whisper-small-uk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="h9LtLSb/whisper-small-uk")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("h9LtLSb/whisper-small-uk") model = AutoModelForSpeechSeq2Seq.from_pretrained("h9LtLSb/whisper-small-uk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5627546f563253630efc86f1e7c9ea9ba038ff6d1d1d68c00ef337afac77c82e
- Size of remote file:
- 967 MB
- SHA256:
- e3e928d3d6cb9b81ac19813591cc19f22f1421c65595c0072c02bc497e63bd3a
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