Instructions to use Jeevesh8/init_bert_ft_qqp-40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-40 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-40")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-40") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-40") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4d86120f8d777b98226878b6b7bba30f3daafebea20ca79e31e606d297fccbe
- Size of remote file:
- 438 MB
- SHA256:
- 411f558950801790232fad5a872db911756b511066575a18b9bea1deb1266366
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