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:
- 3f7a3f4be224c2cdfab1a6a83bcceb166519bf367c7a112b7394485595bb7bda
- Size of remote file:
- 1.26 GB
- SHA256:
- cb50fa82a148cf7ac2824bf4889397a97fc03d91cecf1f7c0839a122b6d1526a
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