Update README.md

README.md

@@ -101,7 +101,7 @@ print(query_model("Space X Engineer"))
 - The descriptions are synthetically generated. For critical applications, users should validate the content.
 
 ## Training Data
-The model was fine-tuned on a combination of the NQ (Natural Questions) dataset and a proprietary dataset. The NQ dataset was instrumental in teaching the model how to answer questions effectively and enabled several passes for coherent knowledge transfer. The proprietary dataset was synthesized using several advanced prompt engineering techniques with the Microsoft Semantic Kernel and GPT-3.5-turbo, ensuring the generation of profession-specific AI prompts.
+The model was fine-tuned on a combination of the NQ (Natural Questions) dataset and a proprietary dataset. The NQ dataset was instrumental in teaching the model how to answer questions effectively and enabled several passes for coherent knowledge transfer. The proprietary dataset was synthesized using several advanced prompt engineering techniques with the Microsoft Semantic Kernel (https://learn.microsoft.com/en-us/semantic-kernel/overview/) and GPT-3.5-turbo, ensuring the generation of profession-specific AI prompts.
 
 ## Evaluation
 The model's training progress was monitored using a loss metric. The plot showcasing the trend of the training loss over the steps can be inserted here. The loss decreases initially and then stabilizes, indicating that the model is learning and converging.