diff --git a/.github/FUNDING.yml b/.github/FUNDING.yml
new file mode 100644
index 00000000..87a36a6b
--- /dev/null
+++ b/.github/FUNDING.yml
@@ -0,0 +1,15 @@
+# These are supported funding model platforms
+
+github: [KaihuaTang]
+patreon: # Replace with a single Patreon username
+open_collective: # Replace with a single Open Collective username
+ko_fi: # Replace with a single Ko-fi username
+tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel
+community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry
+liberapay: # Replace with a single Liberapay username
+issuehunt: # Replace with a single IssueHunt username
+lfx_crowdfunding: # Replace with a single LFX Crowdfunding project-name e.g., cloud-foundry
+polar: # Replace with a single Polar username
+buy_me_a_coffee: tkhchipaomg
+thanks_dev: # Replace with a single thanks.dev username
+custom: ['https://kaihuatang.github.io/donate']
diff --git a/DATASET.md b/DATASET.md
index 60ab16ee..3b411328 100644
--- a/DATASET.md
+++ b/DATASET.md
@@ -7,3 +7,8 @@ Note that our codebase intends to support attribute-head too, so our ```VG-SGG.h
 1. Download the VG images [part1 (9 Gb)](https://cs.stanford.edu/people/rak248/VG_100K_2/images.zip) [part2 (5 Gb)](https://cs.stanford.edu/people/rak248/VG_100K_2/images2.zip). Extract these images to the file `datasets/vg/VG_100K`. If you want to use other directory, please link it in `DATASETS['VG_stanford_filtered']['img_dir']` of `maskrcnn_benchmark/config/paths_catelog.py`. 
 2. Download the [scene graphs](https://1drv.ms/u/s!AmRLLNf6bzcir8xf9oC3eNWlVMTRDw?e=63t7Ed) and extract them to `datasets/vg/VG-SGG-with-attri.h5`, or you can edit the path in `DATASETS['VG_stanford_filtered_with_attribute']['roidb_file']` of `maskrcnn_benchmark/config/paths_catalog.py`.
 
+### Backup Download Links
+Thanks for the sponsorship from [Catchip](https://github.com/Catchip), we now provide some backup download links for VG-SGG-with-attri.h5 and other files.
+1. [Baidu](https://pan.baidu.com/s/1oyPQBDHXMQ5Tsl0jy5OzgA) Extraction code：1234
+2. [Weiyun](https://share.weiyun.com/ViTWrFxG)
+
diff --git a/README.md b/README.md
index a61db5ed..6f8e6933 100644
--- a/README.md
+++ b/README.md
@@ -6,6 +6,8 @@
 
 Our paper [Unbiased Scene Graph Generation from Biased Training](https://arxiv.org/abs/2002.11949) has been accepted by CVPR 2020 (Oral).
 
+[Support my open source work](https://kaihuatang.github.io/donate.html)
+
 ## Recent Updates
 
 - [x] 2020.06.23 Add no graph constraint mean Recall@K (ng-mR@K) and no graph constraint Zero-Shot Recall@K (ng-zR@K) [\[link\]](METRICS.md#explanation-of-our-metrics)
@@ -71,12 +73,13 @@ After you download the [Faster R-CNN model](https://1drv.ms/u/s!AmRLLNf6bzcir8xe
 The above pretrained Faster R-CNN model achives 38.52/26.35/28.14 mAp on VG train/val/test set respectively.
 
 ## Alternate links
+Thanks for sponsorship from [Catchip](https://github.com/Catchip). Since OneDrive links might be broken in mainland China, we also provide the following alternate links for all the pretrained models and dataset annotations: 
 
-Since OneDrive links might be broken in mainland China, we also provide the following alternate links for all the pretrained models and dataset annotations using BaiduNetDisk: 
-
-Link：[https://pan.baidu.com/s/1oyPQBDHXMQ5Tsl0jy5OzgA](https://pan.baidu.com/s/1oyPQBDHXMQ5Tsl0jy5OzgA)
+Link1(Baidu)：[https://pan.baidu.com/s/1oyPQBDHXMQ5Tsl0jy5OzgA](https://pan.baidu.com/s/1oyPQBDHXMQ5Tsl0jy5OzgA)
 Extraction code：1234
 
+Link2(Weiyun): [https://share.weiyun.com/ViTWrFxG](https://share.weiyun.com/ViTWrFxG)
+
 ## Faster R-CNN pre-training
 The following command can be used to train your own Faster R-CNN model:
 ```bash