Instructions to use SRDdev/QuAC-QA-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/QuAC-QA-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="SRDdev/QuAC-QA-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SRDdev/QuAC-QA-BERT") model = AutoModelForQuestionAnswering.from_pretrained("SRDdev/QuAC-QA-BERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed7bc6ed8198d6b17a6caf67f6f4ef9679ace39a314f7a682868226cea1e803f
- Size of remote file:
- 3.58 kB
- SHA256:
- acdc32753c122f153a9de6b5dd891ad72628fd33f0971548d9a6f1796f99c0bb
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