Instructions to use Jeevesh8/init_bert_ft_qqp-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-4") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c286bf82df8f9456dc8aa95a497fbb3b2e0cc23317d363d2922157746affb444
- Size of remote file:
- 438 MB
- SHA256:
- e8240d795f96253805541906103d7b3214ed88279f6ef9f7ea49f5a679eb8d25
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