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README.md

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-license: apache-2.0
-
-datasets:
-	- ProteinKG25
-
-	
-# OntoProtein
-[OntoProtein](https://openreview.net/pdf?id=yfe1VMYAXa4), the first general framework that makes use of structure in GO (Gene Ontology) into protein pre-training models. We construct a novel large-scale knowledge graph that consists of GO and its related proteins, and gene annotation texts or protein sequences describe all nodes in the graph. We propose novel contrastive learning with knowledge-aware negative sampling to jointly optimize the knowledge graph and protein embedding during pre-training.
+---
+language: protein
+tags:
+- protein language model
+datasets:
+- ProteinKG25
+---
+	
+# OntoProtein model
+Pretrained model on protein sequences using masked language modeling (MLM) and knowledge embedding (KE) objective objective. It was introduced in [this paper](https://openreview.net/pdf?id=yfe1VMYAXa4) and first released in [this repository](https://github.com/zjunlp/OntoProtein). This model is trained on uppercase amino acids: it only works with capital letter amino acids.
+
+## Model description
+[OntoProtein] is the first general framework that makes use of structure in GO (Gene Ontology) into protein pre-training models. We construct a novel large-scale knowledge graph that consists of GO and its related proteins, and gene annotation texts or protein sequences describe all nodes in the graph. We propose novel contrastive learning with knowledge-aware negative sampling to jointly optimize the knowledge graph and protein embedding during pre-training.
+It was first released in this repository.