Update README.md

README.md

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 ClinicalMobileBERT-i2b2-2010 is a fine-tuned version of the [ClinicalMobileBERT](https://huggingface.co/nlpie/clinical-mobilebert) model on the i2b2-2010 dataset for clinical Named Entity Recognition (NER). The model specialises in recognising entities from three categories: problems, treatments, and tests. The initialisation was conducted using the pre-trained checkpoints of the ClinicalMobileBERT model available on Huggingface.
 
 # Architecture
-The architecture of this model is identical to ClinicalMobileBERT. The model was fine-tuned on the i2b2-2010 dataset for the task of clinical NER. The fine-tuning process targeted three categories of entities: problems, treatments, and tests. 
+The architecture of this model is identical to [ClinicalMobileBERT](https://huggingface.co/nlpie/clinical-mobilebert). The model was fine-tuned on the i2b2-2010 dataset for the task of clinical NER. The fine-tuning process targeted three categories of entities: problems, treatments, and tests. The model has around 25M parameters.
 
 # Use Cases
 This model is useful for NLP tasks in the clinical domain that require identification and classification of problems, treatments, and tests.