Instructions to use yacoubagbane/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yacoubagbane/checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yacoubagbane/checkpoints")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("yacoubagbane/checkpoints") model = AutoModelForCTC.from_pretrained("yacoubagbane/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 361356cdbbc5bd8bcc8649fbda9d71c44ab4a93c3ec0f78102373c499e4b0c00
- Size of remote file:
- 5.14 kB
- SHA256:
- 7ea7ee243c93a580fa02d16ee2cff07de4b51470eaa71490c21184dffa4b7670
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