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README.md
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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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The app will then be available at a local address, such as http://127.0.0.1:7860
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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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create an mturk requestor account associated with your AWS account.
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2. Run `python collect.py` locally.
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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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- 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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---
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An RLHF interface for data collection with [Amazon Mechanical Turk](https://www.mturk.com) and Gradio.
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## Instructions for someone to use for their own project
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### Install dependencies
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First, create a Python virtual environment and install the project's dependencies as follows:
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```bash
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python -m pip install -r requirements.txt
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```
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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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The app will then be available at a local address, such as http://127.0.0.1:7860
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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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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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