Instructions to use Jeevesh8/init_bert_ft_qqp-53 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-53 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-53")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-53") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-53") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3068dc14a332734528c58b189511919260c4e7f257a93537a0a58b0a1f441c3
- Size of remote file:
- 438 MB
- SHA256:
- ae7f99284411f737eb4b1808a54ff1e0b6f780e2013100429afc32dc2f002df8
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