auto-rename

README.md

@@ -26,14 +26,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 [![Model License](https://img.shields.io/badge/Model%20License-CC%20By%20NC%204.0-red.svg)]()
 
-This model is one of our LaMini-LM series in paper "[LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions](https://github.com/mbzuai-nlp/lamini-lm)". This model is a fine-tuned version of [t5-small](https://huggingface.co/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-lm/).  
+This model is one of our LaMini-LM series in paper "[LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions](https://github.com/mbzuai-nlp/lamini-lm)". This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [LaMini-instruction 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-lm/).  
 You can view other LaMini-LM series as follow. Note that not all models are performing as well. Models with ✩ are those with the best overall performance given their size/architecture. More details can be seen in our paper. 
 
 <table>
 <thead>
   <tr>
     <th>Base model</th>
-    <th colspan="4">LaMini series (#parameters)</th>
+    <th colspan="4">LaMini-LM series (#parameters)</th>
   </tr>
 </thead>
 <tbody>
@@ -113,7 +113,7 @@ print("Response": generated_text)
     <a><img src="https://raw.githubusercontent.com/mbzuai-nlp/lamini-lm/main/images/lamini-pipeline.drawio.png" alt="Title" style="width: 100%; min-width: 250px; display: block; margin: auto;"></a>
 </p>
 
-We initialize with [t5-small](https://huggingface.co/t5-small) and fine-tune it on our [LaMini dataset](https://huggingface.co/datasets/MBZUAI/LaMini-instruction). Its total number of parameters is 61M. 
+We initialize with [t5-small](https://huggingface.co/t5-small) and fine-tune it on our [LaMini-instruction dataset](https://huggingface.co/datasets/MBZUAI/LaMini-instruction). Its total number of parameters is 61M. 
 
 ### Training Hyperparameters