Add library_name, correct pretty_name, and improve model card

README.md

@@ -1,24 +1,27 @@
 ---
-license: mit
+base_model:
+- google/muril-large-cased
+datasets:
+- prachuryyaIITG/APTFiNER
 language:
 - brx
+license: mit
 metrics:
 - f1
 - precision
 - recall
-base_model:
-- google/muril-large-cased
 pipeline_tag: token-classification
+library_name: transformers
 tags:
 - NER
 - Named_Entity_Recognition
-pretty_name: APTFiNER Tamil MuRIL
-datasets:
-- prachuryyaIITG/APTFiNER
+pretty_name: APTFiNER Bodo MuRIL
 ---
 
 **MuRIL is fine-tuned on Bodo APTFiNER dataset for Fine-grained Named Entity Recognition.**
 
+This model is part of the work presented in [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
@@ -109,4 +112,4 @@ If you use this model, please cite the following papers:
   pages={2027--2051},
   year={2023}
 }
-```
+```