Instructions to use Jeevesh8/init_bert_ft_qqp-97 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-97 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-97")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-97") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-97") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 145f00d88e3518bf38b572bc1fddf7e51d3034eddd9c683f03802465baeb8aa6
- Size of remote file:
- 438 MB
- SHA256:
- afee20833e12c48a465582998669b61e1363e6a297ea213057f035e072545c14
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