Docs: Update supported Python range to include 3.14 (#20779)

### Summary
Python 3.14 support landed in #20452, which raised requires-python to
<3.15 and added 3.14 to the wheel build matrices, but several
user-facing docs still advertised the old 3.10-3.13 range. This updates
the PyPI wheel readme and the getting-started, building-from-source,
quickstart, beginner-pathway, and Raspberry Pi guides to 3.10-3.14.

Author: rascani

README-wheel.md

@@ -5,7 +5,7 @@ ExecuTorch is to enable wider customization and deployment capabilities of the
 PyTorch programs.
 
 The `executorch` pip package is in beta.
-* Supported python versions: 3.10, 3.11, 3.12, 3.13
+* Supported python versions: 3.10, 3.11, 3.12, 3.13, 3.14
 * Compatible systems: Linux x86_64, Linux aarch64, macOS aarch64
 
 To build a minimal wheel from source, set

docs/source/getting-started.md

@@ -8,7 +8,7 @@ This section is intended to describe the necessary steps to take a PyTorch model
 ## System Requirements
 The following are required to install the ExecuTorch host libraries, needed to export models and run from Python. Requirements for target end-user devices are backend dependent. See the appropriate backend documentation for more information.
 
-- Python 3.10 - 3.13
+- Python 3.10 - 3.14
 - g++ version 7 or higher, clang++ version 5 or higher, or another C++17-compatible toolchain.
 - Linux (x86_64 or ARM64), macOS (ARM64), or Windows (x86_64).
     - Intel-based macOS systems require building PyTorch from source (see [Building From Source](using-executorch-building-from-source.md) for instructions).

docs/source/pathway-beginner.md

@@ -65,7 +65,7 @@ Install ExecuTorch and verify your setup before attempting to export a model.
 
 Install the ExecuTorch Python package, export a MobileNet V2 model using XNNPACK, and run your first inference. This is the canonical entry point for all new users.
 
-**Difficulty:** Beginner | **Prerequisites:** Python 3.10–3.13, PyTorch, g++7+ or clang5+
+**Difficulty:** Beginner | **Prerequisites:** Python 3.10–3.14, PyTorch, g++7+ or clang5+
 :::
 
 ::::

docs/source/pathway-quickstart.md

@@ -66,7 +66,7 @@ Follow the {doc}`llm/llama` guide for the complete Llama export and deployment w
 
 ## The 5-Minute Setup
 
-If you have not yet installed ExecuTorch, run the following in a Python 3.10–3.13 virtual environment:
+If you have not yet installed ExecuTorch, run the following in a Python 3.10–3.14 virtual environment:
 
 ```bash
 pip install executorch

docs/source/quick-start-section.md

@@ -52,7 +52,7 @@ Follow these guides in order to get started with ExecuTorch:
 
 ## Prerequisites
 
-- Python 3.10–3.13
+- Python 3.10–3.14
 - PyTorch 2.9+
 - Basic familiarity with PyTorch model development
 

docs/source/raspberry_pi_llama_tutorial.md

@@ -4,7 +4,7 @@
 
 This tutorial demonstrates how to deploy **Llama models on Raspberry Pi 4/5 devices** using ExecuTorch:
 
-- **Prerequisites**: Linux host machine, Python 3.10-3.13, conda environment, Raspberry Pi 4/5
+- **Prerequisites**: Linux host machine, Python 3.10-3.14, conda environment, Raspberry Pi 4/5
 - **Setup**: Automated cross-compilation using `setup.sh` script for ARM toolchain installation
 - **Export**: Convert Llama models to optimized `.pte` format with quantization options
 - **Deploy**: Transfer binaries to Raspberry Pi and configure runtime libraries
@@ -19,7 +19,7 @@ This tutorial demonstrates how to deploy **Llama models on Raspberry Pi 4/5 devi
 
 **Software Dependencies**:
 
-- **Python 3.10-3.13** (ExecuTorch requirement)
+- **Python 3.10-3.14** (ExecuTorch requirement)
 - **conda** or **venv** for environment management
 - **CMake 3.29.6+**
 - **Git** for repository cloning
@@ -42,7 +42,7 @@ uname -s  # Should output: Linux
 uname -m  # Should output: x86_64
 
 # Check Python version
-python3 --version  # Should be 3.10-3.13
+python3 --version  # Should be 3.10-3.14
 
 # Check required tools
 hash cmake git md5sum 2>/dev/null || echo "Missing required tools"

docs/source/using-executorch-building-from-source.md

@@ -28,7 +28,7 @@ ExecuTorch is tested on the following systems, although it should also work in s
   - Otherwise, Python's built-in virtual environment manager `python venv` is a good alternative.
 * `g++` version 7 or higher, `clang++` version 5 or higher, or another
   C++17-compatible toolchain.
-* `python` version 3.10-3.13
+* `python` version 3.10-3.14
 * `ccache` (optional) - A compiler cache that speeds up recompilation
 * **macOS**
   - `Xcode Command Line Tools`