Instructions to use junehong/whisper_base_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junehong/whisper_base_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="junehong/whisper_base_test")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("junehong/whisper_base_test") model = AutoModel.from_pretrained("junehong/whisper_base_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d64b9280374767754b49384e7821227634edc3028ab86effbc9759a2dbded85f
- Size of remote file:
- 290 MB
- SHA256:
- 3049c0c2b66e8ac4f452681e953136e9844b3c12f65554d080a21118580a8bcb
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