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Topic modeling via sum-to-one constrained Poisson non-negative matrix factorization

Project description

tinytopics

PyPI version License Python versions

Topic modeling via sum-to-one constrained Poisson non-negative matrix factorization, built with PyTorch, runs on both CPUs and GPUs.

Installation

You can install tinytopics from PyPI:

pip3 install tinytopics

Or install the development version from GitHub:

git clone https://github.com/nanxstats/tinytopics.git
cd tinytopics
python3 -m pip install -e .

GPU support

The above will install the CPU version of PyTorch by default. To enable GPU support, follow the PyTorch official guide to install the appropriate PyTorch version.

For example, to install PyTorch for Windows with CUDA 12.4:

pip3 uninstall torch
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124

To manage the PyTorch dependency under a project context using virtual environments, you might want to set up manual sources. For example, using Rye.

Get started

After tinytopics is installed, try the example from the getting started guide or see the speed benchmark.

License

MIT

Project details


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Source Distribution

tinytopics-0.1.3.tar.gz (722.6 kB view hashes)

Uploaded Source

Built Distribution

tinytopics-0.1.3-py3-none-any.whl (8.6 kB view hashes)

Uploaded Python 3

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