Add library_name and link to paper

README.md

@@ -1,24 +1,27 @@
 ---
-license: mit
-language:
-- as
 base_model:
 - google/muril-large-cased
-pipeline_tag: token-classification
-tags:
-- NER
-- Named_Entity_Recognition
-pretty_name: SampurNER Assamese MuRIL
 datasets:
 - prachuryyaIITG/SampurNER
+language:
+- as
+license: mit
 metrics:
 - f1
 - precision
 - recall
+pipeline_tag: token-classification
+library_name: transformers
+tags:
+- NER
+- Named_Entity_Recognition
+pretty_name: SampurNER Assamese MuRIL
 ---
 
 **MuRIL is fine-tuned on Assamese [SampurNER](https://huggingface.co/datasets/prachuryyaIITG/SampurNER) dataset for Fine-grained Named Entity Recognition. It is created using the [EaMaTa](https://github.com/PrachuryyaKaushik/SampurNER/blob/main/SampurNER_AAAI_extended.pdf) framework, utilizing the [Few-NERD](https://huggingface.co/datasets/DFKI-SLT/few-nerd) dataset.** <br>
 
+This model is part of the work 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).
+
 Read the paper: [SampurNER in AAAI-2026](https://github.com/PrachuryyaKaushik/SampurNER/blob/main/SampurNER_AAAI_extended.pdf)
 
 SampurNER Dataset: [datasets/prachuryyaIITG/SampurNER](https://huggingface.co/datasets/prachuryyaIITG/SampurNER)
@@ -108,4 +111,5 @@ If you use this model, please cite the following papers:
     url = "https://aclanthology.org/2021.acl-long.248",
     doi = "10.18653/v1/2021.acl-long.248",
     pages = "3198--3213",
-}
+}
+```