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---
license: cc-by-nc-4.0
language:
- en
tags:
- code
pretty_name: README
---
<!-- # TGB -->
**TGB 2.0**
Overview of the Temporal Graph Benchmark (TGB) pipeline:
- TGB includes large-scale and realistic datasets from five different domains with both dynamic link prediction and node property prediction tasks.
- TGB automatically downloads datasets and processes them into `numpy`, `PyTorch` and `PyG compatible TemporalData` formats.
- Novel TG models can be easily evaluated on TGB datasets via reproducible and realistic evaluation protocols.
- TGB provides public and online leaderboards to track recent developments in temporal graph learning domain.
```
pip install py-tgb
```
### Links and Datasets
The project website can be found [here](https://tgb.complexdatalab.com/).
The API documentations can be found [here](https://shenyanghuang.github.io/TGB/).
all dataset download links can be found at [info.py](https://github.com/shenyangHuang/TGB/blob/main/tgb/utils/info.py)
TGB dataloader will also automatically download the dataset as well as the negative samples for the link property prediction datasets.
if website is unaccessible, please use [this link](https://tgb-website.pages.dev/) instead.
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