Instructions to use NchuNLP/Legal-Document-Question-Answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NchuNLP/Legal-Document-Question-Answering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="NchuNLP/Legal-Document-Question-Answering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("NchuNLP/Legal-Document-Question-Answering") model = AutoModelForQuestionAnswering.from_pretrained("NchuNLP/Legal-Document-Question-Answering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aec423f04b8a17b8b1005597ca2d05c5345b2d48e2bcade8480aa46e679e04c7
- Size of remote file:
- 407 MB
- SHA256:
- 278d02809fc43390a0bb620b0de8ea39a83ef0c760d783b63b78a85855d789a6
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