Instructions to use GleamEyeBeast/ASCEND_Dataset_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GleamEyeBeast/ASCEND_Dataset_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GleamEyeBeast/ASCEND_Dataset_Model")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GleamEyeBeast/ASCEND_Dataset_Model") model = AutoModelForCTC.from_pretrained("GleamEyeBeast/ASCEND_Dataset_Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6649e05eab53717181749eb9982571b88c7b47d4295a9414ade8268950d012a
- Size of remote file:
- 1.27 GB
- SHA256:
- 29716eb8d912df0b0417b5d876f86ce47e4af5e9c33449dd0d0fd9b797f825ce
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