Add library_name and improve metadata

Hi! I'm Niels from the Hugging Face community science team. I noticed that this model is part of the AWED-FiNER project and is compatible with the `transformers` library.

I've opened this PR to:
- Add `library_name: transformers` to the metadata to enable the "Use in Transformers" button and automated code snippets.
- Maintain the `token-classification` pipeline tag for better discoverability.
- Ensure the paper and GitHub repository are clearly linked in the model card.

Thanks for your contribution to the community!

README.md

@@ -1,16 +1,17 @@
 ---
-license: mit
+base_model:
+- FacebookAI/xlm-roberta-large
 datasets:
 - MultiCoNER/multiconer_v2
 language:
 - en
+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 English XLM-RoBERTa
 
 **XLM-RoBERTa is fine-tuned on English [MultiCoNER2](https://huggingface.co/datasets/MultiCoNER/multiconer_v2) dataset for Fine-grained Named Entity Recognition.**
 
+This model is part of the **AWED-FiNER** project, 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).
+
 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
@@ -28,6 +31,7 @@ The tagset of [MultiCoNER2](https://huggingface.co/datasets/MultiCoNER/multicone
   * Product (PROD) : Clothing, Vehicle, Food, Drink, OtherPROD
   * Medical (MED) : Medication/Vaccine, MedicalProcedure, AnatomicalStructure, Symptom, Disease
 
+[**AWED-FiNER collection**](https://huggingface.co/collections/prachuryyaIITG/awed-finer) | [**Paper**](https://huggingface.co/papers/2601.10161) | [**Agentic Tool**](https://github.com/PrachuryyaKaushik/AWED-FiNER) | [**Interactive Demo**](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER)
 
 ## Model performance:
 Precision: 78.29 <br>
@@ -41,8 +45,6 @@ Learning Rate: 5e-5 <br>
 Weight Decay: 0.01 <br>
 Batch Size: 64 <br>
 
-[**AWED-FiNER collection**](https://huggingface.co/collections/prachuryyaIITG/awed-finer) | [**Paper**](https://huggingface.co/papers/2601.10161) | [**Agentic Tool**](https://github.com/PrachuryyaKaushik/AWED-FiNER) | [**Interactive Demo**](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER)
-
 ## Sample Usage of Agentic Tool
 
 The AWED-FiNER agentic tool can be used to interact with expert models trained using this framework. Below is an example:
@@ -94,3 +96,4 @@ If you use this model, please cite the following papers:
   volume={40},
   year={2026}
 }
+```