readme: ---
  language:
  - as 
  - bn
  - gu 
  - hi 
  - kn 
  - ml 
  - mr 
  - or 
  - pa 
  - ta 
  - te 
  license: mit
  datasets:
  - Samanantar
  tags:
  - ner
  - Pytorch
  - transformer
  - multilingual
  - nlp
  - indicnlp
  ---
  
  # IndicNER
  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.
  The 11 languages covered by IndicNER are: Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Punjabi, Tamil, Telugu.
  
  ## Training Corpus
  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.
  
  ## Downloads
  Download from this same Huggingface repo.
  
  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.
  
  ## Usage
  
  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.
  
  <!-- citing information -->
  ## Citing
  
  If you are using IndicNER, please cite the following article:
  ```
  @misc{mhaske2022naamapadam,
    doi = {10.48550/ARXIV.2212.10168},
    url = {https://arxiv.org/abs/2212.10168},
    author = {Mhaske, Arnav and Kedia, Harshit and Doddapaneni, Sumanth and Khapra, Mitesh M. and Kumar, Pratyush and Murthy, Rudra and Kunchukuttan, Anoop},
    title = {Naamapadam: A Large-Scale Named Entity Annotated Data for Indic Languages}
    publisher = {arXiv},
    year = {2022},
    copyright = {arXiv.org perpetual, non-exclusive license}
  }
  
  ```
  We would like to hear from you if:
  
  - You are using our resources. Please let us know how you are putting these resources to use.
  - You have any feedback on these resources.
  
  
  <!-- License -->
  ## License
  
  The IndicNER code (and models) are released under the MIT License.
  
  <!-- Contributors -->
  ## Contributors
   - Arnav Mhaske <sub> ([AI4Bharat](https://ai4bharat.org), [IITM](https://www.iitm.ac.in)) </sub>
   - Harshit Kedia <sub> ([AI4Bharat](https://ai4bharat.org), [IITM](https://www.iitm.ac.in)) </sub>
   - Sumanth Doddapaneni <sub> ([AI4Bharat](https://ai4bharat.org), [IITM](https://www.iitm.ac.in)) </sub>
   - Mitesh M. Khapra <sub> ([AI4Bharat](https://ai4bharat.org), [IITM](https://www.iitm.ac.in)) </sub>
   - Pratyush Kumar <sub> ([AI4Bharat](https://ai4bharat.org), [Microsoft](https://www.microsoft.com/en-in/), [IITM](https://www.iitm.ac.in)) </sub> 
   - Rudra Murthy <sub> ([AI4Bharat](https://ai4bharat.org), [IBM](https://www.ibm.com))</sub>
   - Anoop Kunchukuttan <sub> ([AI4Bharat](https://ai4bharat.org), [Microsoft](https://www.microsoft.com/en-in/), [IITM](https://www.iitm.ac.in)) </sub> 
  
  This work is the outcome of a volunteer effort as part of the [AI4Bharat initiative](https://ai4bharat.iitm.ac.in).
  
  
  <!-- Contact -->
  ## Contact
  - Anoop Kunchukuttan ([anoop.kunchukuttan@gmail.com](mailto:anoop.kunchukuttan@gmail.com))
  - Rudra Murthy V ([rmurthyv@in.ibm.com](mailto:rmurthyv@in.ibm.com))
    