Instructions to use Jeevesh8/init_bert_ft_qqp-75 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-75 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-75")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-75") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-75") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- abe97b9f9bb5cb9617890db838486bbc65b19f85071491ab8b3912dd49295ae7
- Size of remote file:
- 438 MB
- SHA256:
- bf7668f9a359941208e3ad6673530ec6316b5e46d0c0fd13965759108bec7807
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