Instructions to use Jeevesh8/init_bert_ft_qqp-96 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-96 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-96")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-96") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-96") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47e233a28191f9e42f2e152dcd19c75771f26c9e40cf093434514003d9350801
- Size of remote file:
- 438 MB
- SHA256:
- 60e574e5e6309620d88bc5233ce7cd748cddff61adef7ae8dba677f7452461b0
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