I’m sorry but I really don’t understand what should I do with what they say on that page? 
I use CUDA Toolkit 11.1 and the cuDNN of that version. But should I download them or leave them as I have them?


NVIDIA CUDA 12 9.2 or above

NVIDIA cuDNN 9 v7 or above

And with the compiler what i need do? What do I need to download? (As it says that “or above” version I guess it would be fine, right? )


Compiler 1 compatible with CUDA Note: You could refer to the cuDNN Support Matrix 3 for cuDNN versions with the various supported CUDA, CUDA driver and NVIDIA hardwares

And regarding this …
Would I need to disable CUDA Support?

If you want to disable CUDA support, export environment variable USE_CUDA=0. Other potentially useful environment variables may be found in setup.py.

From Jetson Nano I guess I don’t need anything…

If you are building for NVIDIA’s Jetson platforms (Jetson Nano, TX1, TX2, AGX Xavier), Instructions to install PyTorch for Jetson Nano are available here 2


From the ROCm compiler do I need something? or I not need disable nothing?


If you want to compile with ROCm support, install


AMD ROCm 4.0 and above installation


ROCm is currently supported only for Linux system.


If you want to disable ROCm support, export environment variable USE_ROCM=0. Other potentially useful environment variables may be found in setup.py.
If I understood correctly, I should only install this with conda, right?
conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi typing_extensions future six requests dataclasses

or…
conda install -c conda-forge libuv=1.39

is it possible to do this without git? Just downloading the project and running from my terminal?
git clone --recursive https://github.com/pytorch/pytorch
cd pytorch
# if you are updating an existing checkout
git submodule sync
git submodule update --init --recursive