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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 472cd9c508ecac95e5c20bcdd1cd976b91365077986f9dc7a5b56d67b4c7408d
- Size of remote file:
- 1.27 GB
- SHA256:
- ec30b5878efeb5fb5b4806a554da8c4ede6c7f169b6021316e7168de16609889
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