Instructions to use Jeevesh8/init_bert_ft_qqp-74 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-74 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-74")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-74") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-74") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6d7f8500717303e0838984ff78c7d0b9936a06b944b6838646863a1512e5090
- Size of remote file:
- 438 MB
- SHA256:
- d71e96c87b6dd55c75411bc3b27a8a1e901c83814617e23511ea79cd312e4f9f
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