Instructions to use Jeevesh8/init_bert_ft_qqp-48 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-48 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-48")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-48") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-48") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65155bd25fdfed4425a232f0fbbe14fa6c52cc46063618f74cab8fe0dc987c4a
- Size of remote file:
- 438 MB
- SHA256:
- b4911a428385376fc11e1978d28395cc2e7c015d9e682e3e4aaba49374146592
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