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@@ -128,16 +128,14 @@ conda activate BiaPy_env
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Then you will need to install <ahref="https://pypi.org/project/biapy/"target="_blank"rel="noopener noreferrer">BiaPy package</a> and <ahref="https://pytorch.org/get-started/locally/"target="_blank"rel="noopener noreferrer">Pytorch</a>:
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```bash
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pip install biapy
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# To install with GPU support: Pytorch 2.4.0 + CUDA 11.8
The PyPI package does not install <ahref="https://pytorch.org/get-started/locally/"target="_blank"rel="noopener noreferrer">Pytorch</a> because there is no option to build that package specifying exactly the CUDA version you want to use. There are a few solutions to set up ``pyproject.toml`` with poetry and specify the CUDA version, as discussed <ahref="https://github.com/python-poetry/poetry/issues/6409"target="_blank"rel="noopener noreferrer">here</a>, but then PyPI package can not be built (as stated <ahref="https://peps.python.org/pep-0440/#direct-references"target="_blank"rel="noopener noreferrer">here</a>).
@@ -166,19 +164,13 @@ mamba activate BiaPy_env
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Now you need to install <ahref="https://pytorch.org/get-started/locally/"target="_blank"rel="noopener noreferrer">Pytorch</a> and related packages. Double check <ahref="https://pytorch.org/get-started/locally/"target="_blank"rel="noopener noreferrer">Pytorch's official page</a> for its specific installation. For example, to install the lastest version of <ahref="https://pytorch.org/get-started/locally/"target="_blank"rel="noopener noreferrer">Pytorch</a> with ``conda`` installation in Windows OS under CUDA 12.1:
This will create a folder called ``BiaPy`` that contains all the files of the <ahref="https://github.com/BiaPyX/BiaPy"target="_blank"rel="noopener noreferrer">library's official repository</a>. Then you will need to install BiaPy dependencies:
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