Instructions to use Jeevesh8/init_bert_ft_qqp-91 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-91 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-91")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-91") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-91") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea96df1fd797469ef45e46c1b194700e182b7704350bf741c2469cbdfa5e9f55
- Size of remote file:
- 438 MB
- SHA256:
- c315b5ca1a641baab2fdd8573cf9c7cb2dfbe3bfa3fc8e97e68b809fdc90189f
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