Instructions to use Jeevesh8/init_bert_ft_qqp-45 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-45 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-45")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-45") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-45") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af4b731942f6aef72bcd0a4061b2a124eca657678a7722f5a7e8f0fb74160415
- Size of remote file:
- 438 MB
- SHA256:
- 2828c82befbcbbd85cdcab2e85c765080bb307b5606c09da2f6f6d87cc47b81f
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