DeepMoji and torchMoji

The torchMoji implementation is a PyTorch port of the original DeepMoji model, making them ecosystem siblings where torchMoji provides an alternative framework-specific implementation of the same underlying architecture.

DeepMoji
51
Established
torchMoji
51
Established
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Stars: 1,551
Forks: 311
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 922
Forks: 189
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About DeepMoji

bfelbo/DeepMoji

State-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc.

Built on Keras with Theano/TensorFlow backends, the model leverages 1.2 billion tweets to learn emoji-emotion associations, then applies transfer learning for fine-tuning on custom datasets. Extracts 2304-dimensional emotional feature vectors and predicts emoji distributions for new text, enabling both direct emoji classification and downstream task adaptation. A PyTorch alternative (torchMoji) is available via HuggingFace for modern workflows.

About torchMoji

huggingface/torchMoji

😇A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc

Built on 1.2 billion tweets with emoji supervision, the model learns emotional representations transferable to downstream tasks via fine-tuning. The architecture extracts 2304-dimensional emotional feature vectors from text and predicts emoji distributions, enabling both direct emoji classification and transfer learning for sentiment/sarcasm detection on custom datasets. Integrates with scikit-learn and the emoji library for preprocessing and analysis workflows.

Scores updated daily from GitHub, PyPI, and npm data. How scores work