Instructions to use Jeevesh8/bert_ft_qqp-97 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-97 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-97")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-97") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-97") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62920ffbf6ed67afa098a8461be67f5a1336d7d1469155ce09d4e2fd31d0d979
- Size of remote file:
- 438 MB
- SHA256:
- 02667a48f7f953beedcc62abd5eb18e4d6692c93cc2eed243278fc21b7cb7008
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