Instructions to use Chetna19/m_bert_large_qa_model 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 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")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Chetna19/m_bert_large_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("Chetna19/m_bert_large_qa_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7542e76fb7d07d11b68933123aa7f51095cdcbbf399b58ec17c6c0607a488f8
- Size of remote file:
- 1.34 GB
- SHA256:
- 30f22a12fe4ad9e45ea1a9e8abb6a42a52adf342e82ca42a7d516a386ef72a97
路
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