Instructions to use Chetna19/m_bert_base_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chetna19/m_bert_base_qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Chetna19/m_bert_base_qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Chetna19/m_bert_base_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("Chetna19/m_bert_base_qa_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e5808189b05635df2ede908896e6d3a50633deb101e351f1b725a9db08a90e1
- Size of remote file:
- 3.58 kB
- SHA256:
- 8b2bba241b62c72aca17447db3eb26f4c112ccafb38ca52be4c6b87a9d4aeb82
路
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