Spaces:
Runtime error
Runtime error
| title: Dadc | |
| emoji: 🏢 | |
| colorFrom: red | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 3.0.17 | |
| app_file: app.py | |
| pinned: false | |
| license: bigscience-bloom-rail-1.0 | |
| A basic example of dynamic adversarial data collection with a Gradio app. | |
| *Instructions for someone to use for their own project:* | |
| **Setting up the Space** | |
| 1. Clone this repo and deploy it on your own Hugging Face space. | |
| 2. Add one of your Hugging Face tokens to the secrets for your space, with the | |
| name `HF_TOKEN`. Now, create an empty Hugging Face dataset on the hub. Put | |
| the url of this dataset in the secrets for your space, with the name | |
| `DATASET_REPO_URL`. It can be a private or public dataset. When you run this | |
| space on mturk in the following lines, the app will use your token to | |
| automatically store new hits to your dataset. | |
| **Running Data Collection** | |
| 1. On your local repo that you pulled, create a copy of `config.py.example`, | |
| just called `config.py`. Now, put keys from your AWS account in `config.py`. | |
| These keys should be for an AWS account that has the | |
| AmazonMechanicalTurkFullAccess permission. You also need to | |
| create an mturk requestor account associated with your AWS account. | |
| 2. Run `python collect.py` locally. If you run it with the `--live_mode` flag, | |
| it launches HITs on mturk, using the app you deployed on the space as the | |
| data collection UI and backend. NOTE: this means that you will need to pay | |
| real workers. If you don't use the `--live_mode` flag, then it will run the | |
| HITs on mturk sandbox, which is identical to the normal mturk, but just for | |
| testing. You can create a worker account and go to the sandbox version to | |
| test your HIT. | |
| **Profit** | |
| Now, you should be watching hits come into your Hugging Face dataset | |
| automatically! | |