Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Stable Diffusion Webui | 103,308 | 10 hours ago | 2 | January 17, 2022 | 1,515 | agpl-3.0 | Python | |||
Stable Diffusion web UI | ||||||||||
Pytorch | 71,055 | 3,341 | 6,728 | 6 hours ago | 37 | May 08, 2023 | 12,781 | other | Python | |
Tensors and Dynamic neural networks in Python with strong GPU acceleration | ||||||||||
Netron | 24,046 | 4 | 69 | a day ago | 587 | August 01, 2023 | 23 | mit | JavaScript | |
Visualizer for neural network, deep learning, and machine learning models | ||||||||||
Pytorch Cyclegan And Pix2pix | 20,036 | 4 months ago | 493 | other | Python | |||||
Image-to-Image Translation in PyTorch | ||||||||||
Tutorials | 7,274 | 2 days ago | 196 | bsd-3-clause | Python | |||||
PyTorch tutorials. | ||||||||||
Deepo | 6,312 | 8 months ago | 1 | mit | Python | |||||
Setup and customize deep learning environment in seconds. | ||||||||||
Bigdl | 4,384 | 10 | 9 hours ago | 16 | April 19, 2021 | 831 | apache-2.0 | Jupyter Notebook | ||
Accelerating LLM with low-bit (INT3 / INT4 / NF4 / INT5 / INT8) optimizations using bigdl-llm | ||||||||||
Gluonts | 3,791 | 12 | 6 days ago | 92 | August 07, 2023 | 359 | apache-2.0 | Python | ||
Probabilistic time series modeling in Python | ||||||||||
Artificial Intelligence Deep Learning Machine Learning Tutorials | 3,436 | 3 months ago | 152 | other | Python | |||||
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more. | ||||||||||
Chatbot | 3,252 | 3 months ago | 88 | Python | ||||||
ChatGPT带火了聊天机器人,主流的趋势都调整到了GPT类模式,本项目也与时俱进,会在近期更新GPT类版本。基于本项目和自己的语料可以训练出自己想要的聊天机器人,用于智能客服、在线问答、闲聊等场景。 |
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):
tutorial
so that the file name is your_tutorial.py
.beginner_source
, intermediate_source
, advanced_source
directory 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 prototype_source
.toctree
directive and create a customcarditem
in index.rst... 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
, thensource venv/bin/activate
.
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-noplot
to 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 neural_style_transfer_tutorial.py
, run:
GALLERY_PATTERN="neural_style_transfer_tutorial.py" make html
or
GALLERY_PATTERN="neural_style_transfer_tutorial.py" sphinx-build . _build
The GALLERY_PATTERN
variable respects regular expressions.