Instructions to use Jeevesh8/bert_ft_qqp-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-0") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c7a958c521e2c9803d7d90de611ee98ecf20c3f7d74e6184650aa52f9f94946
- Size of remote file:
- 438 MB
- SHA256:
- 45b6067aff8811ba2a9e73ea79b9b96b140278a72bc71c39461d2284a14b97e7
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