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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 one of your Hugging Face tokens to the secrets for your space, with the |
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name `HF_TOKEN`. Now, create an empty Hugging Face dataset on the hub. Put |
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the url of this dataset in the secrets for your space, with the name |
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`DATASET_REPO_URL`. It can be a private or public dataset. When you run this |
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space on mturk and when people visit your space on huggingface.co, the app |
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will use your token to automatically store new HITs in your dataset. NOTE: |
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if you push something to your dataset manually, you need to restart your space |
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or it could get merge conflicts when trying to push HIT data. |
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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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- If you are developing and running this space locally to test it out, try |
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deleting the data directory that the app clones before running the app again. |
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Otherwise, the app could get merge conflicts when storing new HITs on the hub. |
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When you redeploy your app on Hugging Face spaces, the data directory is deleted |
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automatically. |
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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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