Instructions to use Jeevesh8/init_bert_ft_qqp-99 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-99 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-99")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-99") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-99") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfe8dbbef4c4402cb478497d261116c7c48dd5129140771be32e75f0d0e43243
- Size of remote file:
- 438 MB
- SHA256:
- 28901c9ccc486db4a71355fd36326fde3cb862db0365de47648bc77f1b4d23cc
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