Add library_name to metadata and improve model card documentation

Hi! I'm Niels from the Hugging Face community science team.

This PR adds the `library_name: transformers` metadata tag to your model card. This will enable the "Use in Transformers" button and generate an automated code snippet on the model page, making it easier for users to load and use your model.

I have also kept your excellent documentation regarding the MultiCoNER2 dataset, model performance, and the sample usage for the AWED-FiNER agentic tool.

README.md

@@ -1,24 +1,27 @@
 ---
-license: mit
+base_model:
+- FacebookAI/xlm-roberta-large
 datasets:
 - MultiCoNER/multiconer_v2
 language:
 - de
+license: mit
 metrics:
 - f1
 - precision
 - recall
-base_model:
-- FacebookAI/xlm-roberta-large
 pipeline_tag: token-classification
 tags:
 - NER
 - Named_Entity_Recognition
 pretty_name: MultiCoNER2 German XLM-RoBERTa
+library_name: transformers
 ---
 
 **XLM-RoBERTa is fine-tuned on German [MultiCoNER2](https://huggingface.co/datasets/MultiCoNER/multiconer_v2) dataset for Fine-grained Named Entity Recognition.**
 
+This model is part of the [AWED-FiNER](https://huggingface.co/papers/2601.10161) framework, providing fine-grained NER solutions.
+
 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}
-}
+}
+```