Update README.md

README.md

@@ -60,15 +60,16 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This model is a long-form text generation model based on the Longformer Encoder-Decoder (LED) architecture. The LED architecture extends the Transformer model to handle long documents by incorporating sparse attention mechanisms. This makes it suitable for tasks such as summarization of lengthy patent documents, where traditional models might struggle with context length limitations. The model has been fine-tuned on the BigPatent dataset, a large collection of patent documents, to enhance its performance in generating concise and informative summaries.
 
 ## Intended uses & limitations
 
-More information needed
+Intended uses
+- Patent summarization: Generate concise summaries of patent documents.
+- Long document summarization: Useful for summarizing other types of long-form documents beyond patents.
 
-## Training and evaluation data
-
-More information needed
+Limitations
+- Context length: Although LED handles long documents better than standard Transformers, extremely lengthy documents might still present challenges.
 
 ## Training procedure