Merge pull request thuml#229 from alienishi/main

docs: Corrected minute grammatical errors in README.md

Author: wuhaixu2016

README.md

@@ -17,7 +17,8 @@ Till October 2023, the top three models for five different tasks are:
 | 🥈 2nd            |   [PatchTST](https://github.com/yuqinie98/PatchTST)    | [Non-stationary<br/>Transformer](https://github.com/thuml/Nonstationary_Transformers) | [Non-stationary<br/>Transformer](https://github.com/thuml/Nonstationary_Transformers) | [Non-stationary<br/>Transformer](https://github.com/thuml/Nonstationary_Transformers) | [FEDformer](https://github.com/MAZiqing/FEDformer) |
 | 🥉 3rd            | [TimesNet](https://arxiv.org/abs/2210.02186) | [FEDformer](https://github.com/MAZiqing/FEDformer)           | [Autoformer](https://github.com/thuml/Autoformer)            | [Informer](https://github.com/zhouhaoyi/Informer2020)        | [Autoformer](https://github.com/thuml/Autoformer)  |
 
-**Note: We will keep updating this leaderboard.** If you have proposed advanced and awesome models, you are welcome to send your paper/code link to us or raise a pull request. We will add them to this repo and update the leaderboard as soon as possible.
+
+**Note: We will keep updating this leaderboard.** If you have proposed advanced and awesome models, you can send us your paper/code link or raise a pull request. We will add them to this repo and update the leaderboard as soon as possible.
 
 **Compared models of this leaderboard.** ☑ means that their codes have already been included in this repo.
   - [x] **iTransformer** - iTransformer: Inverted Transformers Are Effective for Time Series Forecasting [[arXiv 2023]](https://arxiv.org/abs/2310.06625) [[Code]](https://github.com/thuml/Time-Series-Library/blob/main/models/iTransformer.py)
@@ -98,7 +99,7 @@ If you have any questions or suggestions, feel free to contact:
 - Haoran Zhang (z-hr20@mails.tsinghua.edu.cn)
 - Jiawei Guo (guo-jw21@mails.tsinghua.edu.cn)
 
-or describe it in Issues. Recently, Jiawei Guo is the main maintainer of this library 😊.
+Or describe it in Issues.
 
 ## Acknowledgement
 
@@ -112,7 +113,7 @@ This library is constructed based on the following repos:
 
 - Classification: https://github.com/thuml/Flowformer
 
-All the experiment datasets are public and we obtain them from the following links:
+All the experiment datasets are public, and we obtain them from the following links:
 
 - Long-term Forecasting and Imputation: https://github.com/thuml/Autoformer