Fix metadata inconsistencies, add library_name and paper/code links

README.md

@@ -1,23 +1,29 @@
 ---
-license: mit
+base_model:
+- FacebookAI/xlm-roberta-large
+datasets:
+- prachuryyaIITG/APTFiNER
 language:
 - as
+license: mit
 metrics:
 - f1
 - precision
 - recall
-base_model:
-- google/muril-large-cased
 pipeline_tag: token-classification
 tags:
 - NER
 - Named_Entity_Recognition
-pretty_name: APTFiNER Tamil MuRIL
-datasets:
-- prachuryyaIITG/APTFiNER
+pretty_name: APTFiNER Assamese XLM-R
+library_name: transformers
 ---
 
-**MuRIL is fine-tuned on Assamese APTFiNER dataset for Fine-grained Named Entity Recognition.**
+**This model is fine-tuned on the Assamese APTFiNER dataset for Fine-grained Named Entity Recognition.**
+
+It is part of the **AWED-FiNER** collection, as 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).
+
+- **Code:** [GitHub - AWED-FiNER](https://github.com/PrachuryyaKaushik/AWED-FiNER)
+- **Interactive Demo:** [Hugging Face Space](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER)
 
 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:
 
@@ -109,4 +115,4 @@ If you use this model, please cite the following papers:
   pages={2027--2051},
   year={2023}
 }
-```
+```