Instructions to use Jeevesh8/init_bert_ft_qqp-98 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-98 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-98")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-98") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-98") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd94a2e1873a1bb1afd095285c4e8286b6ddb53f27c000f4e52e40cd8a828042
- Size of remote file:
- 438 MB
- SHA256:
- 0bab2af2e9eba58382e348de89f339501b02fa45a07bc0c65b9cd08f40acdda2
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