Estimating Carbon Emissions of HuggingFace AI Models

This repository contains the code for analyzing CO2 emissions data from Hugging Face models, as well as a Firefox extension for predicting carbon emissions of Autotrain Hugging Face models. The analysis is conducted using statistics.py to gather dataset statistics and ml_models.py to perform linear regression and random forest regression on the dataset.

Repository Structure

statistics.py: Python script for gathering statistics of the dataset.
ml_models.py: Python script for performing linear regression and random forest regression on the dataset.
Ecolabel/: Folder containing the code for the Firefox extension.
Python_server/: Folder containing the Flask backend code for the Firefox extension.

Installation and Usage

Analysis

statistics.py and ml_models.py can be ran as is with python {file}.py.

Firefox Extension

1. Load the extension into Firefox:
   • Open Firefox and type about:debugging in the address bar.
   • Click on "This Firefox" in the left-hand menu.
   • Click on "Load Temporary Add-on" and navigate to the manifest.json file in the Ecolabel/ folder.
   • Select the manifest.json file to load the extension.
2. Once the extension is loaded, you can use it by following these steps:
   • Click on the extension icon in the toolbar.
   • Select the domain of your machine learning model (NLP, Computer Vision, or Other).
   • Enter the size of your dataset in bytes.
   • The extension will provide you with a prediction of carbon emissions in grams.

Flask server

Is hosted and referred to by the extension, but the code could be hosted from flask_app.py. The extension will need adjusted routing in that case.

Contributors

Thijs Nulle (@thijsnulle)
Petter Reijalt (@Petter6)
Harmen Kroon (@HarmenKroon)