Code implementation of Transformer Model in "Attention is All You Need" in PyTorch.
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Updated
Jun 3, 2024 - Jupyter Notebook
Code implementation of Transformer Model in "Attention is All You Need" in PyTorch.
Robust Point Cloud Processing through Positional Embedding
Transformers - Basics
Code for "The Locality and Symmetry of Positional Encodings" EMNLP Findings
This is a novel Transformer network based approach to distinguish ChatGPT generated Text from Human text. The model was also deployed on local server using Flask where Docker was used to manage all dependencies.
Annotated vanilla implementation in PyTorch of the Transformer model introduced in 'Attention Is All You Need'.
Comparison of positional encoding schemes in transformer
完整的原版transformer程序,complete origin transformer program
Codebase of paper "Balancing structure and position information in Graph Transformer network with a learnable node embedding"
The implementation of transformer as presented in the paper "Attention is all you need" from scratch.
Positional encoding example
This repository provides a complete workflow for text processing using Hugging Face Transformers and NLTK. It includes modules for sentence normalization, spelling correction, word embedding generation, positional encoding computation, and English-to-French translation
Transformer based chatbot based on "Attention is all you need"
Official code for NeurIPS 2023 paper "Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding".
Unofficial pytorch implementation of the paper "Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding", NeurIPS 2021.
Basis invariance synthetic experiment in Appendix D of NeurIPS 2023 paper "Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding".
Transformer translator website with multithreaded web server in Rust
Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding - Tensorflow
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