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--- |
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language: |
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- as |
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- bn |
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- gu |
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- hi |
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- kn |
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- ml |
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- mr |
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- or |
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- pa |
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- ta |
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- te |
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license: mit |
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datasets: |
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- Samanantar |
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tags: |
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- ner |
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- Pytorch |
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- transformer |
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- multilingual |
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- nlp |
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- indicnlp |
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--- |
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# IndicNER |
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IndicNER is a model trained to complete the task of identifying named entities from sentences in Indian languages. Our model is specifically fine-tuned to the 11 Indian languages mentioned above over millions of sentences. The model is then benchmarked over a human annotated testset and multiple other publicly available Indian NER datasets. |
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The 11 languages covered by IndicNER are: Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Punjabi, Tamil, Telugu. |
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## Training Corpus |
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Our model was trained on a [dataset](https://huggingface.co/datasets/ai4bharat/naamapadam) which we mined from the existing [Samanantar Corpus](https://huggingface.co/datasets/ai4bharat/samanantar). We used a bert-base-multilingual-uncased model as the starting point and then fine-tuned it to the NER dataset mentioned previously. |
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## Downloads |
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Download from this same Huggingface repo. |
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Update 20 Dec 2022: We released a new paper documenting IndicNER and Naamapadam. We have a different model reported in the paper. We will update the repo here soon with this model. |
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## Usage |
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You can use [this Colab notebook](https://colab.research.google.com/drive/1sYa-PDdZQ_c9SzUgnhyb3Fl7j96QBCS8?usp=sharing) for samples on using IndicNER or for finetuning a pre-trained model on Naampadam dataset to build your own NER models. |
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<!-- citing information --> |
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## Citing |
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If you are using IndicNER, please cite the following article: |
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``` |
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@misc{mhaske2022naamapadam, |
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doi = {10.48550/ARXIV.2212.10168}, |
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url = {https://arxiv.org/abs/2212.10168}, |
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author = {Mhaske, Arnav and Kedia, Harshit and Doddapaneni, Sumanth and Khapra, Mitesh M. and Kumar, Pratyush and Murthy, Rudra and Kunchukuttan, Anoop}, |
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title = {Naamapadam: A Large-Scale Named Entity Annotated Data for Indic Languages} |
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publisher = {arXiv}, |
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year = {2022}, |
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copyright = {arXiv.org perpetual, non-exclusive license} |
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} |
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``` |
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We would like to hear from you if: |
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- You are using our resources. Please let us know how you are putting these resources to use. |
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- You have any feedback on these resources. |
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<!-- License --> |
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## License |
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The IndicNER code (and models) are released under the MIT License. |
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<!-- Contributors --> |
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## Contributors |
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- Arnav Mhaske <sub> ([AI4Bharat](https://ai4bharat.org), [IITM](https://www.iitm.ac.in)) </sub> |
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- Harshit Kedia <sub> ([AI4Bharat](https://ai4bharat.org), [IITM](https://www.iitm.ac.in)) </sub> |
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- Sumanth Doddapaneni <sub> ([AI4Bharat](https://ai4bharat.org), [IITM](https://www.iitm.ac.in)) </sub> |
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- Mitesh M. Khapra <sub> ([AI4Bharat](https://ai4bharat.org), [IITM](https://www.iitm.ac.in)) </sub> |
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- Pratyush Kumar <sub> ([AI4Bharat](https://ai4bharat.org), [Microsoft](https://www.microsoft.com/en-in/), [IITM](https://www.iitm.ac.in)) </sub> |
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- Rudra Murthy <sub> ([AI4Bharat](https://ai4bharat.org), [IBM](https://www.ibm.com))</sub> |
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- Anoop Kunchukuttan <sub> ([AI4Bharat](https://ai4bharat.org), [Microsoft](https://www.microsoft.com/en-in/), [IITM](https://www.iitm.ac.in)) </sub> |
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This work is the outcome of a volunteer effort as part of the [AI4Bharat initiative](https://ai4bharat.iitm.ac.in). |
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<!-- Contact --> |
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## Contact |
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- Anoop Kunchukuttan ([anoop.kunchukuttan@gmail.com](mailto:anoop.kunchukuttan@gmail.com)) |
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- Rudra Murthy V ([rmurthyv@in.ibm.com](mailto:rmurthyv@in.ibm.com)) |
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