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NVIDIA-NeMo
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NVIDIA-NeMo/Megatron-Bridge

Training library for Megatron-based models with bidirectional Hugging Face conversion capability

Python ◇ developer-tools Apache-2.0
★938STARS
⑂520FORKS
!473ISSUES
🏆#3,004GLOBAL RANK
🔥4DAYS TRENDING
🚀
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Star History

Continuous Observations
Interactive star growth chart for NVIDIA-NeMo/Megatron-Bridge
CSV

Momentum

+23

STARS · LAST 30 DAYS

1

PER DAY

#381

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+7+23+90
Per day111
Forks gained+3+10+26

Megatron-Bridge gained 23 stars in the last 30 days, about 1 a day, and now has 938. It is about 1 year old and has averaged roughly 938 stars a year. It ranks #381 among Python repositories and #3,004 across all languages on GitHubRepo.

Trending Record

Megatron-Bridge has maintained a continuous presence across global trending indexes, peaking at #973. Below is the 30-day activity profile:

💡 Overview

Megatron-Bridge is an open-source project written in Python: Training library for Megatron-based models with bidirectional Hugging Face conversion capability.

Engineered for speed, consistency, and developer ease, it solves common hurdles in Python. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Python for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ pip install Megatron-Bridge

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

Megatron-Bridge coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Production System Integration

Embed Megatron-Bridge into Python backend services to handle core application logic.

CI/CD Automated Pipelines

Run automated validation, builds, and integration suites during deployments.

Developer Tooling & Workflows

Accelerate developer onboarding with pre-configured project utilities.

Open Source Extension

Fork and customize internal modules under the repository's open Apache-2.0 license.

🚀 Getting Started

1

Install Megatron-Bridge using your package manager: `pip install Megatron-Bridge`

2

Initialize your project workspace or configuration file for Megatron-Bridge.

3

Import Megatron-Bridge into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `Megatron-Bridge --help` to verify successful setup.

👍 Strengths

Active community backing with 938 GitHub stars and verified adoption.
Permissive open-source distribution under the Apache-2.0 license.
Built in Python for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Python and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

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👥 Who Should Use This

Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

NVIDIA-NeMo/Megatron-Bridge is currently ranked #3,004 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#2,999 Hyundai-Kia-Connect/kia_uvo Python ★ 941 Compare ↗
#2,999 huggingface/AnyLanguageModel Swift ★ 941 Compare ↗
#2,999 microsoft/power-platform-skills JavaScript ★ 941 Compare ↗
#2,999 google/sam Go ★ 941 Compare ↗
#3,003 openvinotoolkit/model_server C++ ★ 939 Compare ↗
#3,004 NVIDIA-NeMo/Megatron-Bridge This Project Python ★ 938
#3,004 mojombo/clippy — ★ 938 Compare ↗
#3,004 facebook/openr C++ ★ 938 Compare ↗
#3,004 SMGCommunity/Petari C++ ★ 938 Compare ↗
#3,004 repoprompt/repoprompt-ce Swift ★ 938 Compare ↗
#3,009 ejmahler/RustFFT Rust ★ 937 Compare ↗

Frequently Asked Questions

What does Megatron-Bridge do? +

Training library for Megatron-based models with bidirectional Hugging Face conversion capability

What language is Megatron-Bridge written in? +

The primary language is Python. Topics include: software.

Is Megatron-Bridge actively maintained? +

Yes, the last recorded push was on Sep 28, 2026 with 473 open issues being tracked.

How many stars does Megatron-Bridge have? +

Megatron-Bridge has 938 stars and 520 forks on GitHub.

How does Megatron-Bridge rank among GitHub repositories? +

With 938 stars, NVIDIA-NeMo/Megatron-Bridge is ranked #3,004 globally across all repositories tracked on GitHubRepo and #381 among Python projects.

What license is Megatron-Bridge distributed under? +

The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.

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