Instructions to use Jeevesh8/init_bert_ft_qqp-82 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-82 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-82")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-82") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-82") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a114e4d5044a9112cfe9da05fadf1b67ac0d48cf17fa279bc15067aced96981
- Size of remote file:
- 438 MB
- SHA256:
- 4299a1062d619a6df921cae08d1bb362ccdca5cf21401f996527daeb2babe50a
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