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:
- 68eef76e784f9a5007c15ef12f6f2a034a6a5b62e3c9f80d3d66488306bee84b
- Size of remote file:
- 3.06 kB
- SHA256:
- 2800217239fdba7c41f9fb70c9cdaf3f40b5f987a8e497da4b1859e11451bd37
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