Instructions to use beom115/temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beom115/temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="beom115/temp")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("beom115/temp") model = AutoModelForSpeechSeq2Seq.from_pretrained("beom115/temp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59e369fc470601e8b18be3c185180f63b35c6eba0fe2651fca680014b191d2d8
- Size of remote file:
- 4.66 kB
- SHA256:
- 8f926e74f2dbe8b8684deed2143a6a3815fee009a353aef279a80235363350a0
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