Update README.md

README.md

@@ -12,7 +12,7 @@ pipeline_tag: token-classification
 #  NER Model using Roberta
 
 
-This markdown presents a Robustly Optimized BERT Pretraining Approach (RoBERTa) model trained on a combination of two diverse datasets for two languages: English and Persian. The English dataset used is [CoNLL 2003](), while the Persian dataset is [PEYMA-ARMAN-Mixed](), a fusion of the "PEYAM" and "ARMAN" datasets, both popular for Named Entity Recognition (NER) tasks.
+This markdown presents a Robustly Optimized BERT Pretraining Approach (RoBERTa) model trained on a combination of two diverse datasets for two languages: English and Persian. The English dataset used is [CoNLL 2003](https://huggingface.co/datasets/conll2003), while the Persian dataset is [PEYMA-ARMAN-Mixed](https://huggingface.co/datasets/AliFartout/PEYMA-ARMAN-Mixed), a fusion of the "PEYAM" and "ARMAN" datasets, both popular for Named Entity Recognition (NER) tasks.
 
 The model training pipeline involves the following steps: