Instructions to use Jeevesh8/init_bert_ft_qqp-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-32")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-32") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-32") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea5d8708b6d94fa9202c07b51155b8bf8ea32b444ab20b511e638582f9602fdb
- Size of remote file:
- 438 MB
- SHA256:
- d397fdbe77a28f8889c77547d06c8af67ddaf3c6f69c9d7a05a5e5b23b3c717d
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