Instructions to use Jeevesh8/roberta_base_qqp_ft_54 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/roberta_base_qqp_ft_54 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/roberta_base_qqp_ft_54")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/roberta_base_qqp_ft_54") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/roberta_base_qqp_ft_54") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 638fb713226facb82f6215095d0b160f46c5b6d01a1c3944a2b7aa277575ca69
- Size of remote file:
- 499 MB
- SHA256:
- 9f4c33fee0e0fed06b09a3b159f39d6b935c09dd47a08020f03b3e2dfb6bcfcf
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