Instructions to use monideep2255/batch_size_16_og with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monideep2255/batch_size_16_og with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="monideep2255/batch_size_16_og")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("monideep2255/batch_size_16_og") model = AutoModelForCTC.from_pretrained("monideep2255/batch_size_16_og") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab483d031dc7875acd6f10f8212692a7eb0014f9e0efcf6dcd56a51bea0d6196
- Size of remote file:
- 1.26 GB
- SHA256:
- 58fe56c74d6d46f4d3e7bf4e143c197e6e46a70e1369c46b55aca7af2f71db38
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