Update README.md

Add link for public dataset.

README.md

@@ -44,7 +44,7 @@ The "Mistral-7B-Retail-v2" uses the `MistralForCausalLM` structure with a `Llama
 
 This model was trained with a dataset specifically designed for retail-related question and answer interactions. The dataset encompasses a comprehensive range of retail intents, ensuring the model is trained to handle diverse customer inquiries and scenarios. It includes 46 distinct intents such as `add_product`, `availability_in_store`, `cancel_order`, `pay`, `refund_policy`, `track_order`, `use_app`, and many more, reflecting common retail transactions and customer service interactions. Each intent contains 1000 examples, which helps in creating responses across various retail situations.
 
-This extensive training dataset ensures that the model can understand and respond to a wide array of retail-related queries, providing support in customer service applications. The dataset follows a structured approach, similar to other datasets published on Hugging Face, but is specifically tailored to cater to the retail sector.
+This extensive training dataset ensures that the model can understand and respond to a wide array of retail-related queries, providing support in customer service applications. The dataset follows a structured approach, similar to other datasets published on Hugging Face, but is specifically tailored to cater to the customer support sector: [bitext/Bitext-customer-support-llm-chatbot-training-dataset](https://huggingface.co/datasets/bitext/Bitext-customer-support-llm-chatbot-training-dataset)
 
 ## Training Procedure