Instructions to use ngohuudang/test_bug2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ngohuudang/test_bug2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ngohuudang/test_bug2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ngohuudang/test_bug2") model = AutoModelForCTC.from_pretrained("ngohuudang/test_bug2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec052ba3a41f0152b30d06aa5cbf723a7db0dcc3ac1779d561407b8e41c89e60
- Size of remote file:
- 378 MB
- SHA256:
- 22d53afde9ebe7d30b4bbfa2f9c03d21c45d0be84d7f63126e2d3f8799860c12
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