Instructions to use Jeevesh8/init_bert_ft_qqp-47 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-47 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-47")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-47") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-47") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd8dd4abf783feb6555da25a4214e7f9487ee53efea04cbd955aee921484e3f5
- Size of remote file:
- 438 MB
- SHA256:
- b1ae079b84b3c7f712499fecc1b1a8c231936ee9ee57c5a773e5b04f9ceabc63
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