Instructions to use zasheza/Part1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zasheza/Part1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="zasheza/Part1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("zasheza/Part1") model = AutoModelForCTC.from_pretrained("zasheza/Part1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- deac6bbbfa81abdb4de96ff27b566ff398631b7a55e4564e39e3acd37c1cffdb
- Size of remote file:
- 2.8 kB
- SHA256:
- 6e9ce685063098bf14f2f5edaa190b2155739da05c077e1db3a45737a397074a
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