Instructions to use Jeevesh8/init_bert_ft_qqp-72 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-72 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-72")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-72") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-72") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 382589aef14da436479a1aad9d6125e5e02f647047b680ec65fd3c20caecdff5
- Size of remote file:
- 438 MB
- SHA256:
- 446234e92675af00253ba49685c88bda249a34c149f74d859c2486f820239a54
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