XDoc

Introduction

Citation

@article{chen2022xdoc,
  title={XDoc: Unified Pre-training for Cross-Format Document Understanding},
  author={Chen, Jingye and Lv, Tengchao and Cui, Lei and Zhang, Cha and Wei, Furu},
  journal={arXiv preprint arXiv:2210.02849},
  year={2022}
}

• Original Model Card
• question-answering Task on Hugging Face

Send Request

curl <AZUREML_ENDPOINT_URL> \
    -X POST \
    -H "Authorization: Bearer <AZUREML_TOKEN>" \
    -H "Content-Type: application/json" \
    -d '{"question": "What is my name?", "context": "My name is Clara and I live in Berkeley."}'

Supported Parameters

• inputs (object): One (context, question) pair to answer
  • context (string): The context to be used for answering the question
  • question (string): The question to be answered
• parameters (object):
  • top_k (integer): The number of answers to return (will be chosen by order of likelihood). Note that we return less than topk answers if there are not enough options available within the context.
  • doc_stride (integer): If the context is too long to fit with the question for the model, it will be split in several chunks with some overlap. This argument controls the size of that overlap.
  • max_answer_len (integer): The maximum length of predicted answers (e.g., only answers with a shorter length are considered).
  • max_seq_len (integer): The maximum length of the total sentence (context + question) in tokens of each chunk passed to the model. The context will be split in several chunks (using docStride as overlap) if needed.
  • max_question_len (integer): The maximum length of the question after tokenization. It will be truncated if needed.
  • handle_impossible_answer (boolean): Whether to accept impossible as an answer.
  • align_to_words (boolean): Attempts to align the answer to real words. Improves quality on space separated languages. Might hurt on non-space-separated languages (like Japanese or Chinese)