Update introduction_en.ipynb (#5721)

modelcenter/PP-HelixFold/introduction_en.ipynb

@@ -7,11 +7,11 @@
    "source": [
     "## 1. PP-HelixFold Introduction\n",
     "\n",
-    "AlphaFold2 is an accurate protein structure prediction pipeline. PP-HelixFold provides an efficient and improved implementation of the complete training and inference pipelines of AlphaFold2 in GPU and DCU. Compared with the computational performance of AlphaFold2 reported in the paper and OpenFold implemented through PyTorch, PP-HelixFold reduces the training time from about 11 days to 7.5 days. Training PP-HelixFold from scratch can achieve competitive accuracy with AlphaFold2.\n",
+    "AlphaFold2 is an accurate protein structure prediction pipeline. PP-HelixFold provides an efficient and improved implementation of the complete training and inference pipelines of AlphaFold2 in GPU and DCU. Compared with the computational performance of AlphaFold2 reported in the paper and OpenFold implemented through PyTorch, PP-HelixFold reduces the training time from about 11 days originally to 5.12 days, and only 2.89 days when using hybrid parallelism. Training HelixFold from scratch can achieve competitive accuracy with AlphaFold2.\n",
     "\n",
     "<p align=\"center\">\n",
-    "<img src=\"https://github.com/PaddlePaddle/PaddleHelix/blob/dev/.github/HelixFold_computational_performance.png?raw=true\" align=\"middle\" height=\"50%\" width=\"50%\" />\n",
-    "<img src=\"https://github.com/PaddlePaddle/PaddleHelix/blob/dev/.github/HelixFold_accuracy.png?raw=true\" align=\"middle\" height=\"60%\" width=\"60%\" />\n",
+    "<img src=\"https://github.com/PaddlePaddle/PaddleHelix/blob/dev/.github/HelixFold_computational_perf.png?raw=true\" align=\"middle\" height=\"50%\" width=\"50%\" />\n",
+    "<img src=\"https://github.com/PaddlePaddle/PaddleHelix/blob/dev/.github/HelixFold_infer_accuracy.png?raw=true\" align=\"middle\" height=\"60%\" width=\"60%\" />\n",
     "</p>\n",
     "\n",
     "\n",