Update README.md

README.md

@@ -16,7 +16,7 @@ TAPEX was proposed in [TAPEX: Table Pre-training via Learning a Neural SQL Execu
 
 TAPEX (**Ta**ble **P**re-training via **Ex**ecution) is a conceptually simple and empirically powerful pre-training approach to empower existing models with *table reasoning* skills. TAPEX realizes table pre-training by learning a neural SQL executor over a synthetic corpus, which is obtained by automatically synthesizing executable SQL queries.
 
-TAPEX is based on the BART architecture, the transformer encoder-encoder (seq2seq) model with a bidirectional (BERT-like) encoder and an autoregressive (GPT-like) decoder.
+TAPEX is based on the BART architecture, the transformer encoder-decoder (seq2seq) model with a bidirectional (BERT-like) encoder and an autoregressive (GPT-like) decoder.
 
 This model is the `tapex-base` model fine-tuned on the [WikiTableQuestions](https://huggingface.co/datasets/wikitablequestions) dataset.