Update model card metadata and improve documentation

This PR improves the model repository by:
- Updating the `pipeline_tag` to `other` as per the community science team's guidelines.
- Adding the `library_name: transformers` tag to enable automated code snippets and better discoverability.
- Correcting the `pretty_name` from "Tamil" to "Marathi" to match the model's actual language (`mr`).
- Adding a link to the research paper on Hugging Face Papers.
- Including a link to the official GitHub repository for the AWED-FiNER project.

README.md

@@ -1,24 +1,27 @@
 ---
-license: mit
+base_model:
+- google/muril-large-cased
+datasets:
+- prachuryyaIITG/APTFiNER
 language:
 - mr
+license: mit
 metrics:
 - f1
 - precision
 - recall
-base_model:
-- google/muril-large-cased
-pipeline_tag: token-classification
+pipeline_tag: other
+library_name: transformers
 tags:
 - NER
 - Named_Entity_Recognition
-pretty_name: APTFiNER Tamil MuRIL
-datasets:
-- prachuryyaIITG/APTFiNER
+pretty_name: APTFiNER Marathi MuRIL
 ---
 
 **MuRIL is fine-tuned on Marathi APTFiNER dataset for Fine-grained Named Entity Recognition.**
 
+This model is a part of the [AWED-FiNER collection](https://huggingface.co/collections/prachuryyaIITG/awed-finer), presented in the paper [AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers](https://huggingface.co/papers/2601.10161).
+
 The tagset of [MultiCoNER2](https://huggingface.co/datasets/MultiCoNER/multiconer_v2) is a fine-grained tagset. The fine to coarse level mapping of the tags are as follows:
 
   * Location (LOC) : Facility, OtherLOC, HumanSettlement, Station
@@ -48,7 +51,7 @@ Batch Size: 64 <br>
 [Prof. V Vijaya Saradhi](https://www.linkedin.com/in/vijaya-saradhi-a90a604/) <br>
 [Prof. Ashish Anand](https://www.linkedin.com/in/anandashish/)
 
-APTFiNER is a part of the [AWED-FiNER collection](https://huggingface.co/collections/prachuryyaIITG/awed-finer). Please check: [**Paper**](https://huggingface.co/papers/2601.10161) | [**Agentic Tool**](https://github.com/PrachuryyaKaushik/AWED-FiNER) | [**Interactive Demo**](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER)
+APTFiNER is a part of the [AWED-FiNER collection](https://huggingface.co/collections/prachuryyaIITG/awed-finer). Please check: [**Paper**](https://huggingface.co/papers/2601.10161) | [**GitHub Repository**](https://github.com/PrachuryyaKaushik/AWED-FiNER) | [**Interactive Demo**](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER)
 
 ## Sample Usage
 
@@ -104,9 +107,5 @@ If you use this model, please cite the following papers:
 
 @inproceedings{fetahu2023multiconer,
   title={MultiCoNER v2: a Large Multilingual dataset for Fine-grained and Noisy Named Entity Recognition},
-  author={Fetahu, Besnik and Chen, Zhiyu and Kar, Sudipta and Rokhlenko, Oleg and Malmasi, Shervin},
-  booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
-  pages={2027--2051},
-  year={2023}
-}
+  author={Fetahu, Besnik and Chen, Zhiyu}
 ```