Hello trend,
This is Satya Mallick from LearnOpenCV.com.
We present to you a highly requested article about Transformers! It is part of a long series of blog posts on Vision Transformers. In today's post, we understand the fundamentals of how Transformers work and how the Self-attention mechanism works and how to implement it in PyTorch.
Specifically, you will learn about:
- Evolution of Attention Mechanism with basics of RNN & LSTMs.
- Neural Self-Attention
- QKV and Attention Matrix
- Multi-Head Self Attention
- Formulation of Self-Attention Mechanism
- PyTorch Implementation of Self-Attention
Without further ado, let's jump into the post:
Attention Mechanism in Transformers |
Reminder
In case you missed out on our previous announcement: We are running an AI Art Generation Contest for our upcoming Kickstarter campaign for "Mastering AI Art Generation with Stable Diffusion".
The winner gets an iPad Air and the Top 10 finalists win our latest course.
OpenCV AI Art Generation Contest Submission |
We can't wait to see what you come up with and are excited to see how our community of AI, art, and science enthusiasts can bring this campaign to life.
Join us in celebrating the potential of AI to create beautiful and meaningful works of art.
Cheers!
Satya
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