Update README.md

README.md

@@ -23,7 +23,7 @@ should probably proofread and complete it, then remove this comment. -->
 [![Code License](https://img.shields.io/badge/Code%20License-Apache_2.0-green.svg)](https://github.com/tatsu-lab/stanford_alpaca/blob/main/LICENSE)
 [![Data License](https://img.shields.io/badge/Data%20License-CC%20By%20NC%204.0-red.svg)](https://github.com/tatsu-lab/stanford_alpaca/blob/main/DATA_LICENSE)
 
-This model is one of our LaMini model series in paper "[LaMini: A Diverse Herd of Distilled Models from Large-Scale Instructions]()". This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on [LaMini dataset]() that contains 2.58M samples for instruction fine-tuning. For more information about our dataset, please refer to our [project repository](https://github.com/mbzuai-nlp/lamini/).  
+This model is one of our LaMini model series in paper "[LaMini: A Diverse Herd of Distilled Models from Large-Scale Instructions]()". This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on [LaMini dataset](https://huggingface.co/datasets/MBZUAI/LaMini-instruction) that contains 2.58M samples for instruction fine-tuning. For more information about our dataset, please refer to our [project repository](https://github.com/mbzuai-nlp/lamini/).  
 You can view other LaMini model series as follow. Note that not all models are performing as well. More details can be seen in our paper. 
 
 <table>
@@ -86,7 +86,7 @@ You can view other LaMini model series as follow. Note that not all models are p
 ## Use
 
 ### Intended use
-We recommend to use model to reponse to human instructions wrote in natural language. 
+We recommend using the model to response to human instructions written in natural language. 
 
 We now show you how to load and use our model using HuggingFace `pipline()`. 
 
@@ -105,7 +105,7 @@ print("Response": generated_text)
 ```
 
 ## Training Procedure
-We initialize with [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) and fine-tune it on our [LaMini dataset](). Its total number of parameters is 61M. 
+We initialize with [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) and fine-tune it on our [LaMini dataset](https://huggingface.co/datasets/MBZUAI/LaMini-instruction). Its total number of parameters is 61M. 
 
 ### Training Hyperparameters