Instructions to use Svetlana0303/Regression_bert_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Svetlana0303/Regression_bert_7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Svetlana0303/Regression_bert_7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Svetlana0303/Regression_bert_7") model = AutoModelForSequenceClassification.from_pretrained("Svetlana0303/Regression_bert_7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87f6945c4c165650f8e053b7dc22c2ade8582d4618f7055b9520ce53d8ad1a6c
- Size of remote file:
- 268 MB
- SHA256:
- 826ed147867acab9360580bd2cb96f7ad192257939867b5dfb0eaf46b1f00c0e
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