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Adapter bert-base-multilingual-uncased-hinglish-sentiment for bert-base-multilingual-uncased

Note: This adapter was not trained by the AdapterHub team, but by these author(s): Meghana Bhange, Nirant K. See author details below.

Adapter for Hinglish Sentiment Analysis, based on SemEval 2020 Task 9

This adapter was created for usage with the Adapters library.

Usage

First, install adapters:

pip install -U adapters

Now, the adapter can be loaded and activated like this:

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("bert-base-multilingual-uncased")
adapter_name = model.load_adapter("AdapterHub/bert-base-multilingual-uncased-hinglish-sentiment")
model.set_active_adapters(adapter_name)

Architecture & Training

  • Adapter architecture: pfeiffer
  • Prediction head: classification
  • Dataset: Hinglish Sentiment

Author Information

Citation

@article{Hinglish,
    title={HinglishNLP: Fine-tuned Language Models for Hinglish Sentiment Detection},
    author={Meghana Bhange,
            Nirant Kasliwal,
    journal={ArXiv},
    year={2020}
}

This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/nirantk/bert-base-multilingual-uncased-hinglish-sentiment.yaml.

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