Update README.md

README.md

@@ -27,7 +27,11 @@ inference: false
 
 # bart-large-cnn-finetuned-samsum-lora
 
-This model is a further fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the [samsum](https://huggingface.co/datasets/samsum) dataset.  The base model [bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) is a fine-tuned verstion of BART model on the [CNN Daily Mail](https://huggingface.co/datasets/cnn_dailymail) dataset.
+This model is a further fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the [samsum](https://huggingface.co/datasets/samsum) dataset.  
+
+The base model [bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) is a fine-tuned verstion of BART model on the [CNN Daily Mail](https://huggingface.co/datasets/cnn_dailymail) dataset.
+
+Check out [sooolee/flan-t5-base-cnn-samsum-lora](https://huggingface.co/sooolee/flan-t5-base-cnn-samsum-lora) the model fine-tuned for the same purpose.
 
 ## Model description
 
@@ -62,7 +66,7 @@ Input texts longer than 4000 words can be converted into a list of sub-texts wit
 Even though the model checkpoint is small, a huge input would crash the memory. Batching the inputs is advised. 
 Rule of thumb is that T4 can handle at a time a list of upto 14-15 elements, with each elements having 4000 words.
 
-Note 'max_new_tokens=60' is used to limit the summary size. BART model has max generation length = 142 (default) and min generation length = 56.
+Note 'max_new_tokens=60' is used in the example below to limit the summary size. BART model has max generation length = 142 (default) and min generation length = 56.
 
 ```python
 import torch