Instructions to use Prathyusha101/aug_10_x_lr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prathyusha101/aug_10_x_lr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prathyusha101/aug_10_x_lr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Prathyusha101/aug_10_x_lr") model = AutoModelForSequenceClassification.from_pretrained("Prathyusha101/aug_10_x_lr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08c84befa8fa22c531f43bdd6e418ef08cecbfc55b2df09aac2f055436c612b7
- Size of remote file:
- 1.82 GB
- SHA256:
- a0798f294b3ab1c34e80c0cd48e641f363d0cbe061a2149ccc89898f2b9ad571
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