Instructions to use Isma/some_cool_project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isma/some_cool_project with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Isma/some_cool_project")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Isma/some_cool_project") model = AutoModelForCTC.from_pretrained("Isma/some_cool_project") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0d4c8155ed1cef60d6b8b351aeca773db576115d3b23f582d08313abafa0f73
- Size of remote file:
- 378 MB
- SHA256:
- 88f3b7f0b428625594e8b778bcba623018231e64daba6ed541076fa790c8e45d
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