# Requesting GCP credits

**URL:** <https://community.drivendata.org/t/requesting-gcp-credits/3811>\
**Category:** Mapping Disaster Risk from Aerial Imagery\
**Created:** [November 10, 2019, 9:08pm UTC](https://community.drivendata.org/t/requesting-gcp-credits/3811 "2019-11-10T21:08:30Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![sushant3095](https://avatars.discourse-cdn.com/v4/letter/s/e47c2d/32.png) [@sushant3095](https://community.drivendata.org/u/sushant3095)\
**Post date:** [November 10, 2019, 9:08pm UTC](https://community.drivendata.org/t/requesting-gcp-credits/3811/1 "2019-11-10T21:08:30Z")

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It would be great if teams get access to Any cloud vendors. would there be any provision for the same?

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**Author:** ![bkowshik](https://yyz2.discourse-cdn.com/flex028/user_avatar/community.drivendata.org/bkowshik/32/880_2.png) [@bkowshik](https://community.drivendata.org/u/bkowshik)\
**Post date:** [November 30, 2019, 6:56pm UTC](https://community.drivendata.org/t/requesting-gcp-credits/3811/2 "2019-11-30T18:56:59Z")

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👋 @sushant3095

I was able to get up and running for free on Google Colaboratory in about `30 mins` with the following steps.

1. Visit [https://colab.research.google.com/](https://colab.research.google.com/) and create a new Python 3 notebook
2. In the `Runtime` menu, select `Change runtime type` and then select `Hardware accelerator` as `GPU`
3. Download the entire dataset of `~30GB` using `wget`

```auto
wget https://s3.amazonaws.com/drivendata-public-assets/stac.tar

```

1. You will find the dataset available at the path, `/content/stac.tar` in about `15 mins` time

Hope this helps, 😃