Instructions to use Svetlana0303/Regression_bert_NOaug_CustomLoss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Svetlana0303/Regression_bert_NOaug_CustomLoss with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Svetlana0303/Regression_bert_NOaug_CustomLoss")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Svetlana0303/Regression_bert_NOaug_CustomLoss") model = AutoModelForSequenceClassification.from_pretrained("Svetlana0303/Regression_bert_NOaug_CustomLoss", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce28681ce91a320cdafcd2c2ea04dff75bde7e6b7eda26b4de1f4528d71fe72c
- Size of remote file:
- 268 MB
- SHA256:
- 30e8c05722b3865bc1d610d2a739994f637710c5b4596f6d091155149702706a
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