Instructions to use Jeevesh8/bert_ft_qqp-52 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-52 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-52")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-52") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-52") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e928970a2c4e887c290b0fe1b6fce1c95b0806dfb460d5bac57a4a5c009b292a
- Size of remote file:
- 438 MB
- SHA256:
- bb4f6684a8ac141b886892ce25a909d3c9bc735213d116588134fc96af1e6e13
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