Instructions to use Jeevesh8/init_bert_ft_qqp-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-13")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-13") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-13") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6110c890bc2ebb1b733408840466bcff242a7c1785b639a698f475665bd6e5a
- Size of remote file:
- 438 MB
- SHA256:
- 6048e7acdc71490c55378871abd81fc67eba5ff2bc305873b1c0e8a517527fa5
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