Instructions to use Devishri1/test_bert2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devishri1/test_bert2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Devishri1/test_bert2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Devishri1/test_bert2") model = AutoModelForQuestionAnswering.from_pretrained("Devishri1/test_bert2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 061609da32f99c8050c04fab2772606667e316c312e29b91f184130973a9be7a
- Size of remote file:
- 709 MB
- SHA256:
- 1f2d89bedd4f03223aa56152ca2471fd11b5d7f51eac6814deb8e78108b35fe9
路
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