ahmedbesbes/multi-label-sentiment-classifier
How to build a multi-label sentiment classifiers with Tez and PyTorch
This project helps Python developers streamline the creation of multi-label text classification models. It takes in text data labeled with multiple emotions and outputs a trained SqueezeBert model capable of classifying new text for various sentiments. It's designed for machine learning engineers and data scientists building natural language processing applications.
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Use this if you are a Python developer looking for a lightweight wrapper to simplify your PyTorch training pipelines for multi-label text classification tasks.
Not ideal if you are a non-developer seeking a ready-to-use application or a user interface for emotion classification, as this focuses on the model training pipeline.
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Jupyter Notebook
License
MIT
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Last pushed
Feb 28, 2021
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