docs: added platforms list and hardware reqs (#1676)

deeppavlov · Dec 3, 2023 · 432d7a0 · 432d7a0
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diff --git a/README.md b/README.md
@@ -60,8 +60,8 @@ Please leave us [your feedback](https://forms.gle/i64fowQmiVhMMC7f9) on how we c
 
 ## Installation
 
-0. We support `Linux` platform, `Python 3.6`, `3.7`, `3.8`, `3.9` and `3.10`
-    * **`Python 3.5` is not supported!**
+0. DeepPavlov supports `Linux`, `Windows 10+` (through WSL/WSL2), `MacOS` (Big Sur+) platforms, `Python 3.6`, `3.7`, `3.8`, `3.9` and `3.10`.
+    Depending on the model used, you may need from 4 to 16 GB RAM.
 
 1. Create and activate a virtual environment:
     * `Linux`
@@ -99,6 +99,7 @@ By default, DeepPavlov installs models requirements from PyPI. PyTorch from PyPI
 capability. To run supported DeepPavlov models on GPU you should have [CUDA](https://developer.nvidia.com/cuda-toolkit)
 compatible with used GPU and [PyTorch version](deeppavlov/requirements/pytorch.txt) required by DeepPavlov models.
 See [docs](https://docs.deeppavlov.ai/en/master/intro/quick_start.html#using-gpu) for details.
+GPU with Pascal or newer architecture and 4+ GB VRAM is recommended.
 
 ### Command line interface (CLI)
 

diff --git a/docs/intro/installation.rst b/docs/intro/installation.rst
@@ -1,7 +1,8 @@
 Installation
 ============
 
-DeepPavlov supports **Linux** platform, **Python 3.6-3.10**.
+DeepPavlov supports **Linux**, **Windows 10+** (through WSL/WSL2), **MacOS** (Big Sur+) platforms, **Python 3.6-3.10**.
+Depending on the model used, you may need from 4 to 16 GB RAM.
 
 Install with pip
 ~~~~~~~~~~~~~~~~

diff --git a/docs/intro/quick_start.rst b/docs/intro/quick_start.rst
@@ -132,6 +132,7 @@ Using GPU
 To run or train **PyTorch**-based DeepPavlov models on GPU you should have `CUDA <https://developer.nvidia.com/cuda-toolkit>`__
 installed on your host machine, and install model's package requirements. CUDA version should be compatible with
 DeepPavlov :dp_file:`required PyTorch version <deeppavlov/requirements/pytorch.txt>`.
+GPU with Pascal or newer architecture and 4+ GB VRAM is recommended.
 
 .. warning::
     If you use latest NVIDIA architecture, PyTorch installed from PyPI using DeepPavlov could not support your device