Instructions to use Siyam/SKYLy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siyam/SKYLy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Siyam/SKYLy")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Siyam/SKYLy") model = AutoModelForCTC.from_pretrained("Siyam/SKYLy") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1772b6da62ed30e86c1f7a59875de281014680a2fd38f3931355bce5d9f967d
- Size of remote file:
- 1.26 GB
- SHA256:
- ac859d9362c0e51c221d2809bf97b0be2e97257d483d2e8b0d6a776ec685d9f6
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