Transformer_from_scratch_pytorch and Transformer_from_scratch

These two tools are competitors, as both aim to provide an understanding of transformer architecture through implementing it from scratch, with the first being implemented in PyTorch and the second likely a more general explanation or implementation not explicitly tied to a framework.

Maintenance 6/25
Adoption 8/25
Maturity 16/25
Community 14/25
Maintenance 0/25
Adoption 4/25
Maturity 8/25
Community 15/25
Stars: 42
Forks: 7
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 6
Forks: 4
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
No Package No Dependents
No License Stale 6m No Package No Dependents

About Transformer_from_scratch_pytorch

SirawitC/Transformer_from_scratch_pytorch

Build a transformer model from scratch using pytorch to understand its inner workings and gain hands-on experience with deep learning models in PyTorch.

This project provides a detailed guide for machine learning engineers or researchers to build a Transformer model from scratch using PyTorch. It explains each core component like tokenization, positional encoding, and multi-head attention, showing how they fit together. The output is a working Transformer model, ideal for those who want to understand the foundational architecture behind modern NLP models like BERT and GPT.

deep-learning-engineering natural-language-processing model-architecture neural-networks machine-learning-research

About Transformer_from_scratch

leeway0507/Transformer_from_scratch

Transformer 구현 및 학습 방법 설명

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