Instructions to use Chetna19/m_bert_large_qa_model_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chetna19/m_bert_large_qa_model_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Chetna19/m_bert_large_qa_model_2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Chetna19/m_bert_large_qa_model_2") model = AutoModelForQuestionAnswering.from_pretrained("Chetna19/m_bert_large_qa_model_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 711fb94c7d4e945f47de3f66fa4ad643a323dac60bb32730d62945b43caea888
- Size of remote file:
- 1.34 GB
- SHA256:
- 9349a2c9a1883135f960c4c9cc49149bbb83cf0422715d3cba009454ff009d5e
路
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