Add library_name and improve external project links

Hi, I'm Niels from the Hugging Face community team. I'm opening this PR to enhance the model card for better discoverability and usability.

The changes include:
- Adding `library_name: transformers` to the metadata. This enables the "Use in Transformers" code snippet on the model page, making it easier for users to get started with the model.
- Improving the visibility of external project links (paper, GitHub repository, and interactive demo) by moving them to a dedicated section at the top of the model card. This makes it easier for users to quickly find relevant resources.
- Removing the redundant link line from the "Contributors" section, as the links are now prominently featured.

Thank you for your excellent work on the AWED-FiNER collection!

README.md

@@ -1,24 +1,31 @@
 ---
-license: mit
-language:
-- as
 base_model:
 - google/muril-large-cased
-pipeline_tag: token-classification
-tags:
-- NER
-- Named_Entity_Recognition
-pretty_name: CLASSER Assamese MuRIL
 datasets:
 - prachuryyaIITG/CLASSER
+language:
+- as
+license: mit
 metrics:
 - f1
 - precision
 - recall
+pipeline_tag: token-classification
+tags:
+- NER
+- Named_Entity_Recognition
+pretty_name: CLASSER Assamese MuRIL
+library_name: transformers
 ---
 
 **MuRIL is fine-tuned on Assamese [CLASSER](https://huggingface.co/datasets/prachuryyaIITG/CLASSER) dataset for Fine-grained Named Entity Recognition.**
 
+This model is part of the **AWED-FiNER** project, which provides fine-grained NER solutions across 36 languages. 
+
+- **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)
+- **GitHub:** https://github.com/PrachuryyaKaushik/AWED-FiNER
+- **Interactive Demo:** [AWED-FiNER 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:
 
   * Location (LOC) : Facility, OtherLOC, HumanSettlement, Station
@@ -44,8 +51,6 @@ Batch Size: 64 <br>
 [Prachuryya Kaushik](https://www.linkedin.com/in/pkabundant/) <br>
 [Prof. Ashish Anand](https://www.linkedin.com/in/anandashish/)
 
-CLASSER is a part of the [AWED-FiNER collection](https://huggingface.co/collections/prachuryyaIITG/awed-finer). Please check: [**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
 
 The AWED-FiNER agentic tool can be used to interact with expert models trained using this framework. Below is an example:
@@ -106,8 +111,9 @@ If you use this model, please cite the following papers:
 
 @inproceedings{fetahu2023multiconer,
   title={MultiCoNER v2: a Large Multilingual dataset for Fine-grained and Noisy Named Entity Recognition},
-  author={Fetahu, Besnik and Chen, Zhiyu and Kar, Sudipta and Rokhlenko, Oleg and Malmasi, Shervin},
+  author={Fetahu, Besnik and Chen, Zhiyu and Kar, Sudipta and Oleg and Malmasi, Shervin},
   booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
   pages={2027--2051},
   year={2023}
-}
+}
+```