Instructions to use akera/whisper-small-lg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akera/whisper-small-lg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="akera/whisper-small-lg")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("akera/whisper-small-lg") model = AutoModelForSpeechSeq2Seq.from_pretrained("akera/whisper-small-lg") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f83d969d963c8167cfeccf3837014c77e72a8a73aac929a79e99179cb312845
- Size of remote file:
- 3.63 kB
- SHA256:
- e195e3bfe7d12ebb09782ea606340c84ed5a5c69c98acea1bc94f6cdc5f101bb
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