app.py

import gradio as gr
examples = [['D L I P T S S K L V V [MASK] D T S L Q V K K A F F A L V T']] 
description="ProtBert is based on Bert model which pretrained on a large corpus of protein sequences in a self-supervised fashion. This means it was pretrained on the raw protein sequences only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those protein sequences."


At the end, the feature extracted from this model revealed that the LM-embeddings from unlabeled data (only protein sequences) captured important biophysical properties governing protein shape. This implied learning some of the grammar of the language of life realized in protein sequences."

gr.Interface.load("models/Rostlab/prot_bert",  description=description, examples=examples).launch()