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Installation
============
This page covers how to install NVIDIA NeMo for speech AI tasks (ASR, TTS, speaker tasks, audio processing, and speech language models).
Prerequisites
-------------
Before installing NeMo, ensure you have:
#. **Python** 3.12 or above
#. **PyTorch** 2.7+ (install **before** NeMo so CUDA wheels match your GPU driver)
#. **NVIDIA GPU** (required for training; CPU-only inference is possible but slow)
Recommended installation order
------------------------------
Install dependencies in this order when setting up a **local GPU** environment:
#. Create and activate a Python environment.
#. Install a **CUDA toolkit** (or rely on a driver + PyTorch bundle that matches your CUDA major version).
#. Install **PyTorch** (and torchvision if you need it) from the index that matches your CUDA build.
#. Install **NeMo** (from PyPI or editable source) **with the extras** for the collections you need (``asr``, ``tts``, etc.).
Putting PyTorch in place first avoids mismatched CUDA runtimes and makes NeMo’s optional GPU-dependent packages resolve correctly.
**Example (conda + pip, CUDA 13.0 PyTorch wheels):**
.. code-block:: bash
# 1) New environment (adjust Python version if your platform requires it)
conda create -n nemo python=3.12 -y
conda activate nemo
# 2) CUDA toolkit from conda (optional if you already have a compatible toolkit via the driver)
conda install nvidia::cuda-toolkit
# 3) PyTorch built for CUDA 13.x — change cu130 / URL if you use cu124 or CPU-only
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu130
# 4) NeMo: use extras for ASR/TTS/etc. For a clone of the repo, use editable install (see below)
pip install nemo_toolkit[asr,tts]
Adjust the PyTorch ``--index-url`` (e.g. ``cu124``, ``cu121``, or CPU) to match `PyTorch’s install matrix <https://pytorch.org/get-started/locally/>`_ and your NVIDIA driver.
Install from PyPI
-----------------
The quickest way to install NeMo is via pip. Install only the collections you need:
.. code-block:: bash
# Install ASR and TTS (most common)
pip install nemo_toolkit[asr,tts]
# Install everything speech-related
pip install nemo_toolkit[asr,tts,audio]
Available extras:
.. list-table::
:widths: 15 85
:header-rows: 1
* - Extra
- What it includes
* - ``asr``
- Automatic Speech Recognition models, data loaders, and utilities
* - ``tts``
- Text-to-Speech models, vocoders, and audio codecs
* - ``audio``
- Audio processing models (enhancement, separation)
.. _install-from-source:
Install from Source
-------------------
For the latest development version or if you plan to contribute, clone the repository and install in editable mode.
The ``test`` extra pulls in **pytest and tooling for the test suite**. It does **not** install NeMo collection dependencies (ASR, TTS, audio, etc.). Add those extras explicitly or imports like ``nemo.collections.asr`` will fail.
.. code-block:: bash
git clone https://github.com/NVIDIA/NeMo.git
cd NeMo
# After PyTorch is installed (see Recommended installation order above):
# Collections you need for development (required for nemo.collections.* imports)
pip install -e '.[asr,tts]'
# Optional: add test to run pytest with NeMo’s dev test dependencies
# pip install -e '.[asr,tts,test]'
Using Docker
------------
NVIDIA provides Docker containers with NeMo pre-installed. Check the `NeMo GitHub releases <https://github.com/NVIDIA/NeMo/releases>`_ for the latest container tags.
Verify Installation
-------------------
After installing, verify that NeMo is working:
.. code-block:: python
import nemo.collections.asr as nemo_asr
print("NeMo ASR installed successfully!")
# Quick test: load a pretrained model
model = nemo_asr.models.ASRModel.from_pretrained("nvidia/parakeet-tdt-0.6b-v2")
print(f"Model loaded: {model.__class__.__name__}")
What's Next?
------------
- :doc:`ten_minutes` — A quick tour of NeMo's speech capabilities
- :doc:`key_concepts` — Understand the fundamentals of speech AI
- :doc:`choosing_a_model` — Find the right model for your use case
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