Instructions to use monideep2255/batch_size_16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monideep2255/batch_size_16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="monideep2255/batch_size_16")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("monideep2255/batch_size_16") model = AutoModelForCTC.from_pretrained("monideep2255/batch_size_16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56f05b7007ca71db9995b0beed98a5f8653797f236adb8fe3b62f708f00abb5b
- Size of remote file:
- 3.52 kB
- SHA256:
- d31c3f54d7b5db0e62ff842efe30a6fb8ed1bca50716bf0b0efd9a26881f95e2
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