Update README.md

README.md

@@ -13,15 +13,15 @@ model-index:
 The model is intended to be used for Q&A task, given the question & context, the model would attempt to infer the answer text, answer span & confidence score.<br>
 Model is encoder-only (roberta-base) with QuestionAnswering LM Head, fine-tuned on SQUADx dataset with **exact_match:** 86.14 & **f1:** 92.330 performance scores.
 
-[Live Demo: Question Answering Encoders vs Generative](https://huggingface.co/spaces/anshoomehra/question_answering)
+[Live Demo: Question Answering Encoders vs Generative](https://huggingface.co/spaces/consciousAI/question_answering)
 
-Please follow this link for [Generative Question Answering](https://huggingface.co/anshoomehra/question-answering-generative-t5-v1-base-s-q-c/)
+Please follow this link for [Generative Question Answering](https://huggingface.co/consciousAI/question-answering-generative-t5-v1-base-s-q-c/)
 
 Example code:
 ```
 from transformers import pipeline
 
-model_checkpoint = "anshoomehra/question-answering-roberta-base-s"
+model_checkpoint = "consciousAI/question-answering-roberta-base-s"
 
 context = """
 🤗 Transformers is backed by the three most popular deep learning libraries — Jax, PyTorch and TensorFlow — with a seamless integration