Instructions to use Jeevesh8/bert_ft_qqp-87 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-87 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-87")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-87") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-87") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee091ccdb8fad840410c4e69fda926bed141f348c4625378aed475ab98209451
- Size of remote file:
- 438 MB
- SHA256:
- 54a9d702304780b1666320431a16c5d30f9969b4ad5d4f8d7477c783e9d3dff4
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