publish [GPU]: course_UvA-DL/05-transformers-and-MH-attention

Author: Azure Pipelines

.notebooks/course_UvA-DL/05-transformers-and-MH-attention.ipynb

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+oid sha256:e7ce19c647782db988a6ca05c534f8e919f064e314d91fc19730f20b0cbae428
+size 3024932

.notebooks/course_UvA-DL/05-transformers-and-MH-attention.jpg

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+title: 'Tutorial 5: Transformers and Multi-Head Attention'
+author: Phillip Lippe
+created: 2021-06-30
+updated: 2023-03-14
+license: CC BY-SA
+build: 0
+tags:
+- Text
+description: 'In this tutorial, we will discuss one of the most impactful architectures
+  of the last 2 years: the Transformer model.
+
+  Since the paper Attention Is All You Need by Vaswani et al. had been published in
+  2017,
+
+  the Transformer architecture has continued to beat benchmarks in many domains, most
+  importantly in Natural Language Processing.
+
+  Transformers with an incredible amount of parameters can generate long, convincing
+  essays, and opened up new application fields of AI.
+
+  As the hype of the Transformer architecture seems not to come to an end in the next
+  years,
+
+  it is important to understand how it works, and have implemented it yourself, which
+  we will do in this notebook.
+
+  This notebook is part of a lecture series on Deep Learning at the University of
+  Amsterdam.
+
+  The full list of tutorials can be found at https://uvadlc-notebooks.rtfd.io.
+
+  '
+requirements:
+- torchvision
+- matplotlib
+- seaborn
+- lightning>=2.0.0
+accelerator:
+- GPU
+environment:
+- pytorch-lightning==2.0.9.post0
+- lightning==2.3.3
+- setuptools==69.0.3
+- ipython==8.16.1
+- numpy==1.26.4
+- torchvision==0.15.2
+- seaborn==0.13.2
+- torchmetrics==1.2.1
+- matplotlib==3.8.4
+- torch==2.0.1
+- urllib3==2.2.2
+published: '2024-07-19T19:40:50.645247'