File python-stable-diffusion.spec of Package python-stable-diffusion

#
# spec file for package stable-diffusion
#
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%define sname   stable-diffusion
Name:           python-%{sname}
Version:        0.0.1+git.20221116
Release:        0
Summary:        Latent text-to-image diffusion model
License:        CreativeML Open RAIL-M
URL:            https://github.com/CompVis/stable-diffusion
Source:         %{sname}-%{version}.tar.bz2
BuildRequires:	python-rpm-macros
BuildRequires:  %{python_module numpy}
BuildRequires:  %{python_module setuptools}
BuildRequires:  %{python_module tqdm}
Requires:       python-numpy
Requires:       python-torch
Requires:       python-tqdm
%python_subpackages

%description
Stable Diffusion is a latent text-to-image diffusion model. Thanks to a
generous compute donation from Stability AI and support from LAION, we were
able to train a Latent Diffusion Model on 512x512 images from a subset of
the LAION-5B database. Similar to Google's Imagen, this model uses a frozen
CLIP ViT-L/14 text encoder to condition the model on text prompts. With its
860M UNet and 123M text encoder, the model is relatively lightweight and
runs on a GPU with at least 10GB VRAM. See this section below and the model
card.

%prep
%autosetup -n %{sname}-%{version}

%build
%python_build

%install
%python_install

%files %{python_files}
%license LICENSE
%doc README.md
%{python_sitelib}/*

%changelog