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:
- de97cac9a270dae909d8dd4c34609f8ffe5e6ec6c1a259233d5a74ddd416c4cc
- Size of remote file:
- 1.26 GB
- SHA256:
- 5d192fb1205c521511603c887c253a13e250cdb79c164df9f042fe756db81501
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