update readme

README.md

@@ -17,6 +17,9 @@ BART is particularly effective when fine-tuned for text generation (e.g. summari
 
 ## Intended uses & limitations
 
+There have been quite a few issues related to finetuning BART for text generation, and this repo implements solution discussed in [#15559](https://github.com/huggingface/transformers/issues/15559).
+Particularly adding some noise to pre-trained model's BOS embedding. This seems to solve the problem of endless BOS generation for a finetuned BART model. 
+
 You can use the raw model for text infilling. However, the model is mostly meant to be fine-tuned on a supervised dataset. See the [model hub](https://huggingface.co/models?search=bart) to look for fine-tuned versions on a task that interests you.
 
 ### How to use
@@ -26,8 +29,8 @@ Here is how to use this model in PyTorch:
 ```python
 from transformers import BartTokenizer, BartModel
 
-tokenizer = BartTokenizer.from_pretrained('facebook/bart-large')
-model = BartModel.from_pretrained('facebook/bart-large')
+tokenizer = BartTokenizer.from_pretrained('vedu/bart-large-perturbed')
+model = BartModel.from_pretrained('vedu/bart-large-perturbed')
 
 inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
 outputs = model(**inputs)