Update README.md

README.md

@@ -41,7 +41,8 @@ the `rescaling_factor` of the Rotary Embedding layer in the esm model  `num_dna_
 (i.e 6669 for a sequence of 40008 base pairs) and `max_num_tokens_nt` is the max number of tokens on which the backbone nucleotide-transformer was trained on, i.e `2048`. 
 
 [![Open All Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https%3A//huggingface.co/InstaDeepAI/segment_nt/blob/main/inference_segment_nt.ipynb)
-The `./inference_segment_nt.ipynb` can be run in Google Colab by clicking on the icon and shows how to set the rescaling factor and infer on a 50kb genic sequence of the human chromosome 20. 
+The `./inference_segment_nt.ipynb` can be run in Google Colab by clicking on the icon and shows how to handle inference on sequence lengths require changing 
+the rescaling factor and sequence lengths that do not. One can run the notebook and reproduce Fig.1 and Fig.3 from the SegmentNT paper. 
 
 ```python
 # Load model and tokenizer