Add library_name metadata and improve model card structure

README.md

@@ -1,16 +1,17 @@
 ---
-license: mit
+base_model:
+- FacebookAI/xlm-roberta-large
 datasets:
 - MultiCoNER/multiconer_v2
 language:
 - zh
+license: mit
 metrics:
 - f1
 - precision
 - recall
-base_model:
-- FacebookAI/xlm-roberta-large
 pipeline_tag: token-classification
+library_name: transformers
 tags:
 - NER
 - Named_Entity_Recognition
@@ -19,6 +20,8 @@ pretty_name: MultiCoNER2 Chinese XLM-RoBERTa
 
 **XLM-RoBERTa is fine-tuned on Chinese [MultiCoNER2](https://huggingface.co/datasets/MultiCoNER/multiconer_v2) dataset for Fine-grained Named Entity Recognition.**
 
+This model is an expert detector part of the **AWED-FiNER** project, as described 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
@@ -93,4 +96,5 @@ If you use this model, please cite the following papers:
   booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
   volume={40},
   year={2026}
-}
+}
+```