Megatron's multi-modal data loader

Megatron Energon

Report Bug · Request Feature

DISCLAIMER: This package contains research code. APIs may change.

What is this?

Megatron Energon is the multi-modal data loader of Megatron (you can also use it independently).

It's best at

loading large training data to train large multi-modal models
blending many different datasets together
distributing the work across many nodes and processes of a cluster
ensuring reproducibility and resumability
adapting easily to various types of data samples and processing

Try using it together with Megatron Core.

Quickstart

Megatron Energon is a pip-installable python package that offers

dataset-related classes that you can import in your project
a command line utility for data preprocessing and conversion

This document is just a quick start. Please also check out the documentation.

Installation

To install the latest stable version:

pip install megatron-energon

Or to install the current development version:

pip install git+https://github.com/NVIDIA/Megatron-Energon.git

NOTE: We encourage you to install the package (and not just import a local copy). This will ensure you have all the needed dependencies and that you can use the command line tool.

For more details on installing this package, see here.

Usage of command line tool

After installation, the command energon will be available.

Here are some examples for things you can do:

Command	Description
`energon prepare DATASET_ROOT`	Take an existing WebDataset and add the required yaml files to turn it into an energon-compatible dataset
`energon lint DATASET_ROOT`	Verify that the dataset complies with the energon dataset format and that all samples are loadable

Usage of the library

To get started, pick a WebDataset-compliant dataset and run energon prepare DATASET_ROOT on it, to run the interactive assistant and create the .nv-meta folder. As an alternative to WebDataset, Energon also supports the JSONL format, see here.

Once done, try to load it from your Python program:

from megatron.energon import get_train_dataset, get_loader, WorkerConfig


simple_worker_config = WorkerConfig(rank=0, world_size=1, num_workers=2)


train_ds = get_train_dataset(
    '/my/dataset/path',
    batch_size=2,
    shuffle_buffer_size=None,
    max_samples_per_sequence=None,
    worker_config=simple_worker_config,
)

train_loader = get_loader(train_ds)

for batch in train_loader:
    # Do something with batch
    # Infer, gradient step, ...
    pass

For more details, read the documentation.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

megatron_energon-7.4.1.tar.gz (211.3 kB view details)

Uploaded Aug 3, 2026 Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

megatron_energon-7.4.1-py3-none-any.whl (286.8 kB view details)

Uploaded Aug 3, 2026 Python 3

File details

Details for the file megatron_energon-7.4.1.tar.gz.

File metadata

Download URL: megatron_energon-7.4.1.tar.gz
Upload date: Aug 3, 2026
Size: 211.3 kB
Tags: Source
Uploaded using Trusted Publishing? Yes
Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for megatron_energon-7.4.1.tar.gz
Algorithm	Hash digest
SHA256	`31e5511bf894e235dff35dacbe130fb1283010a132b612c07e3fa841cc37d82c`
MD5	`ab64e55069c4916b79af856760a5bfea`
BLAKE2b-256	`81151aa34071dbb64c30f56c68b78989e2a3f11ce72583466b98b37a04206ad4`

See more details on using hashes here.

Provenance

The following attestation bundles were made for megatron_energon-7.4.1.tar.gz:

Publisher: release.yml on NVIDIA/Megatron-Energon

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Statement:
- Statement type: https://in-toto.io/Statement/v1
- Predicate type: https://docs.pypi.org/attestations/publish/v1
- Subject name: megatron_energon-7.4.1.tar.gz
- Subject digest: 31e5511bf894e235dff35dacbe130fb1283010a132b612c07e3fa841cc37d82c
- Sigstore transparency entry: 2334769359
- Sigstore integration time: Aug 3, 2026
Source repository:
- Permalink: NVIDIA/Megatron-Energon@0397ac7f653468851dc0991525c7bc4a51d58d8b
- Branch / Tag: refs/tags/7.4.1
- Owner: https://github.com/NVIDIA
- Access: public
Publication detail:
- Token Issuer: https://token.actions.githubusercontent.com
- Runner Environment: github-hosted
- Publication workflow: release.yml@0397ac7f653468851dc0991525c7bc4a51d58d8b
- Trigger Event: release