|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Pytorch Tutorial||25,860||15 days ago||88||mit||Python|
|PyTorch Tutorial for Deep Learning Researchers|
|Githubdaily||20,449||6 days ago||107|
|坚持分享 GitHub 上高质量、有趣实用的开源技术教程、开发者工具、编程网站、技术资讯。A list cool, interesting projects of GitHub.|
|Awesome Pytorch List||13,786||a month ago||2|
|A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.|
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|Natural Language Processing Tutorial for Deep Learning Researchers|
|The Incredible Pytorch||9,479||25 days ago||1||mit|
|The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.|
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|:mag: Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-3 and alike). Haystack offers production-ready tools to quickly build ChatGPT-like question answering, semantic search, text generation, and more.|
|Pytorch Tutorial||7,372||3 days ago||28||mit||Jupyter Notebook|
|Build your neural network easy and fast, 莫烦Python中文教学|
|Tutorials||6,807||17 hours ago||190||bsd-3-clause||Python|
|Machine Learning Collection||4,993||4 days ago||88||mit||Python|
|A resource for learning about Machine learning & Deep Learning|
|Pytorch Seq2seq||4,356||6 days ago||52||mit||Jupyter Notebook|
|Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.|
All the tutorials are now presented as sphinx style documentation at:
We use sphinx-gallery's notebook styled examples to create the tutorials. Syntax is very simple. In essence, you write a slightly well formatted Python file and it shows up as an HTML page. In addition, a Jupyter notebook is autogenerated and available to run in Google Colab.
Here is how you can create a new tutorial (for a detailed description, see CONTRIBUTING.md):
tutorialso that the file name is
advanced_sourcedirectory based on the level of difficulty. If it is a recipe, add it to
recipes_source. For tutorials demonstrating unstable prototype features, add to the
toctreedirective and create a
.. customcarditem:: beginner/your_tutorial.html. For Recipes, create a thumbnail in the recipes_index.rst
If you are starting off with a Jupyter notebook, you can use this script to convert the notebook to Python file. After conversion and addition to the project, please make sure that section headings and other things are in logical order.
The tutorial build is very large and requires a GPU. If your machine does not have a GPU device, you can preview your HTML build without actually downloading the data and running the tutorial code:
pip install -r requirements.txt.
If you want to use
virtualenv, in the root of the repo, run:
virtualenv venv, then
make docs. This will download the data, execute the tutorials and build the documentation to
docs/directory. This might take about 60-120 min for systems with GPUs. If you do not have a GPU installed on your system, then see next step.
make html-noplotto build basic html documentation to
_build/html. This way, you can quickly preview your tutorial.
If you get ModuleNotFoundError: No module named 'pytorch_sphinx_theme' make: *** [html-noplot] Error 2 from /tutorials/src/pytorch-sphinx-theme or /venv/src/pytorch-sphinx-theme (while using virtualenv), run
python setup.py install.
You can build a single tutorial by using the
GALLERY_PATTERN environment variable. For example to run only
GALLERY_PATTERN="neural_style_transfer_tutorial.py" make html
GALLERY_PATTERN="neural_style_transfer_tutorial.py" sphinx-build . _build
GALLERY_PATTERN variable respects regular expressions.