how_attentive_are_gats
transformer-pytorch
Our great sponsors
| how_attentive_are_gats | transformer-pytorch | |
|---|---|---|
| 1 | 2 | |
| 275 | 2,152 | |
| 6.2% | - | |
| 0.0 | 2.1 | |
| about 2 years ago | 13 days ago | |
| Python | Python | |
| - | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
how_attentive_are_gats
-
Graph Attention Networks (GAT) v2 implementation with side-by-side notes
Code for https://arxiv.org/abs/2105.14491 found: https://github.com/tech-srl/how_attentive_are_gats
transformer-pytorch
-
Is GPT actually using the encoder NOT the decoder part of the transformer?
In the original paper they mention they are only using the decoder part of the model. However, their description and implementations seem to be using the encoder part of the transformer not the encoder. For example, this implementation of the original transformer encoder layer matches what the one in the GPT implementation.
-
[P] Implementation of Transformer with detailed and easy description comments
I implemented the Transformer model of Google Brain using Pytorch. It was specially written together in very detailed and easy explanatory comments. If you're a beginner who wants to implement Transformer, look at my code and try it! Detailed code can be found here. (https://github.com/hyunwoongko/transformer-pytorch)
What are some alternatives?
GAT - Graph Attention Networks (https://arxiv.org/abs/1710.10903)
transformers - š¤ Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
bottleneck - Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
LaTeX-OCR - pix2tex: Using a ViT to convert images of equations into LaTeX code.
pytorch-GAT - My implementation of the original GAT paper (VeliÄkoviÄ et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
BERT-pytorch - Google AI 2018 BERT pytorch implementation
attention-is-all-you-need-pytorch - A PyTorch implementation of the Transformer model in "Attention is All You Need".
minGPT - A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training