Instructions to use monideep2255/batch_size_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monideep2255/batch_size_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="monideep2255/batch_size_2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("monideep2255/batch_size_2") model = AutoModelForCTC.from_pretrained("monideep2255/batch_size_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba86cbba9e769087c14752b96379ea696831d273277b26229dad81ae455f4e3a
- Size of remote file:
- 3.52 kB
- SHA256:
- 6ea8ed9e59d1d7561dc446aeb566a150c024618e7217299fe70a721cb23a4560
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