Instructions to use Jeevesh8/init_bert_ft_qqp-89 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-89 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-89")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-89") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-89") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8908e5da787c64400f386dfe2644d4778127cbf45b5df864382fb082fcdfd63a
- Size of remote file:
- 438 MB
- SHA256:
- f6138aa63d92acce7773354fe11a108f52cd7d6b075797a15e5c2da1f6951744
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