Instructions to use Jeevesh8/bert_ft_qqp-49 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-49 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-49")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-49") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-49") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1c8eacb1959a8a3b1e2e147f7003eea950586db9b1c6716e8c197b2652f116e
- Size of remote file:
- 438 MB
- SHA256:
- 78ba9f4aedfe96eba0e792b798e5653b6e35f1f860b69f8c35cf205879dfb43a
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