Instructions to use Devishri1/test_bert1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devishri1/test_bert1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Devishri1/test_bert1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Devishri1/test_bert1") model = AutoModelForQuestionAnswering.from_pretrained("Devishri1/test_bert1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 973684cba617473c98204d5d707eaa7429b0f6ee590cec14b3aa1a3d0cb5fa15
- Size of remote file:
- 709 MB
- SHA256:
- c37ebffe0e2ce4c37b4aa2f744f0724036e0f7efba27268be13b7d06fce7833f
路
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