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--- |
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title: Dadc |
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emoji: 🏢 |
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colorFrom: red |
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colorTo: gray |
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sdk: gradio |
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sdk_version: 3.0.17 |
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app_file: app.py |
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pinned: false |
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license: bigscience-bloom-rail-1.0 |
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--- |
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A basic example of dynamic adversarial data collection with a Gradio app. |
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**Instructions for someone to use for their own project:** |
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*Setting up the Space* |
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1. Clone this repo and deploy it on your own Hugging Face space. |
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2. Add the following secrets to your space: |
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- `HF_TOKEN`: One of your Hugging Face tokens. |
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- `DATASET_REPO_URL`: The url to an empty dataset that you created the hub. It |
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can be a private or public dataset. |
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- `FORCE_PUSH`: "yes" |
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When you run this space on mturk and when people visit your space on |
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huggingface.co, the app will use your token to automatically store new HITs |
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in your dataset. Setting `FORCE_PUSH` to "yes" ensures that your repo will |
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force push changes to the dataset during data collection. Otherwise, |
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accidental manual changes to your dataset could result in your space gettin |
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merge conflicts as it automatically tries to push the dataset to the hub. For |
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local development, add these three keys to a `.env` file, and consider setting |
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`FORCE_PUSH` to "no". |
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*Running Data Collection* |
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1. On your local repo that you pulled, create a copy of `config.py.example`, |
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just called `config.py`. Now, put keys from your AWS account in `config.py`. |
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These keys should be for an AWS account that has the |
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AmazonMechanicalTurkFullAccess permission. You also need to |
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create an mturk requestor account associated with your AWS account. |
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2. Run `python collect.py` locally. |
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*Profit* |
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Now, you should be watching hits come into your Hugging Face dataset |
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automatically! |
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*Tips and Tricks* |
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- Use caution while doing local development of your space and |
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simultaneously running it on mturk. Consider setting `FORCE_PUSH` to "no" in |
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your local `.env` file. |
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- huggingface spaces have limited computational resources and memory. If you |
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run too many HITs and/or assignments at once, then you could encounter issues. |
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You could also encounter issues if you are trying to create a dataset that is |
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very large. Check the log of your space for any errors that could be happening. |
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