Instructions to use monideep2255/batch_size_32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monideep2255/batch_size_32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="monideep2255/batch_size_32")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("monideep2255/batch_size_32") model = AutoModelForCTC.from_pretrained("monideep2255/batch_size_32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c30c79c6fc14ecfe889beae8a2e00a815bf94968c4c08ac919e48b80ab0960b2
- Size of remote file:
- 3.52 kB
- SHA256:
- e0d87e4ecbeb5c3038c063ad4db59da4fcf22d94f4ab20f87dbcf7ab8f32894a
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