InfoXLM

InfoXLM (NAACL 2021, paper , repo , model ) InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training. MD5

b9d214025837250ede2f69c9385f812c  config.json
bd6b1f392293f0cd9cd829c02971ecd9  pytorch_model.bin
bf25eb5120ad92ef5c7d8596b5dc4046  sentencepiece.bpe.model
eedbd60a7268b9fc45981b849664f747  tokenizer.json

BibTeX

@inproceedings{chi-etal-2021-infoxlm,
  title = "{I}nfo{XLM}: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training",
  author={Chi, Zewen and Dong, Li and Wei, Furu and Yang, Nan and Singhal, Saksham and Wang, Wenhui and Song, Xia and Mao, Xian-Ling and Huang, Heyan and Zhou, Ming},
  booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
  month = jun,
  year = "2021",
  address = "Online",
  publisher = "Association for Computational Linguistics",
  url = "https://aclanthology.org/2021.naacl-main.280",
  doi = "10.18653/v1/2021.naacl-main.280",
  pages = "3576--3588",}

microsoft/infoxlm-base powered by Hugging Face Inference Toolkit

Send Request

You can use cURL or any REST Client to send a request to the AzureML endpoint with your AzureML token.

curl <AZUREML_ENDPOINT_URL> \
    -X POST \
    -H "Authorization: Bearer <AZUREML_TOKEN>" \
    -H "Content-Type: application/json" \
    -d '{"inputs":"The answer to the universe is undefined."}'

Supported Parameters

inputs (string): The text with masked tokens
parameters (object):
- top_k (integer): When passed, overrides the number of predictions to return.
- targets (string[]): When passed, the model will limit the scores to the passed targets instead of looking up in the whole vocabulary. If the provided targets are not in the model vocab, they will be tokenized and the first resulting token will be used (with a warning, and that might be slower).

Check the full API Specification at the Hugging Face Inference documentation .

Model Specifications

LicenseUnknown

Last UpdatedJuly 2025

ProviderHuggingFace

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