Instructions to use Svetlana0303/Regression_BERT_aug_CustomLoss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Svetlana0303/Regression_BERT_aug_CustomLoss with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Svetlana0303/Regression_BERT_aug_CustomLoss")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Svetlana0303/Regression_BERT_aug_CustomLoss") model = AutoModelForSequenceClassification.from_pretrained("Svetlana0303/Regression_BERT_aug_CustomLoss", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b33ee57831b135a6316a988e694cc2425f35d5a718af7bfe105fb5a4097f195
- Size of remote file:
- 268 MB
- SHA256:
- 7d727e4912b0bb47ab1f09639a79630984067ea5c4a7fb2afdf91f3d2c29fff9
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