Instructions to use Jeevesh8/init_bert_ft_qqp-11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-11")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-11") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-11") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 414b46804e69917ee7513fb660a02d4ade2fabe9094f9247c3a86a35f64fda4c
- Size of remote file:
- 438 MB
- SHA256:
- 0f1575485bce7972168f17d7d80b33b99c6a05e6e287bd1f0bd52cca49c5d0fa
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