# Source: https://docs.nvidia.com/nemo-framework/user-guide/latest/libraries/index.html.md

Title: Library Documentation — NVIDIA NeMo Framework User Guide

URL Source: https://docs.nvidia.com/nemo-framework/user-guide/latest/libraries/index.html

Published Time: Thu, 30 Oct 2025 07:07:28 GMT

Markdown Content:
Library Documentation[#](https://docs.nvidia.com/nemo-framework/user-guide/latest/libraries/index.html.md#library-documentation "Link to this heading")
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[NeMo](https://docs.nvidia.com/nemo-framework/user-guide/latest/nemotoolkit/index.html.md), developed by NVIDIA, is a generative AI framework targeting researchers and developers who use PyTorch. Its core purpose is to provide a robust and scalable framework to facilitate the design and implementation of generative AI models. NeMo simplifies access to pre-existing code and pretrained models, helping users from both industry and academia accelerate their development processes. The developer guide offers extensive technical details regarding NeMo’s design, implementation, and optimizations.

[NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/latest/index.html) includes a suite of libraries and recipe collections that help users train models end to end. The AutoModel library (“NeMo AutoModel”) provides Day-0 GPU-accelerated PyTorch training for Hugging Face models. Users can start training and fine-tuning instantly with no conversion delays, and scale effortlessly using PyTorch-native parallelisms, optimized custom kernels, and memory-efficient recipes—all while preserving the original checkpoint format for smooth integration across the Hugging Face ecosystem.

[NeMo Curator](https://docs.nvidia.com/nemo/curator/latest/index.html.md) is a Python library composed of several scalable data-mining modules, specifically designed for curating Natural Language Processing (NLP) data to train large language models (LLMs). It enables NLP researchers to extract high-quality text from vast, uncurated web corpora efficiently, supporting the development of more accurate and powerful language models.

[NeMo Eval](https://docs.nvidia.com/nemo/evaluator/latest/index.html.md) is a comprehensive evaluation module under NeMo Framework for Large Language Models (LLMs). It provides seamless deployment and evaluation capabilities for models trained using NeMo Framework via state-of-the-art evaluation harnesses.

[NeMo Export and Deploy](https://docs.nvidia.com/nemo/export-deploy/latest/index.html.md) provides tools and APIs for exporting and deploying NeMo and Hugging Face models to production environments. It supports various deployment paths including TensorRT, TensorRT-LLM, and vLLM deployment through NVIDIA Triton Inference Server.

[NeMo Megatron Bridge](https://docs.nvidia.com/nemo/megatron-bridge/latest/index.html.md) provides seamless bidirectional conversion between select Hugging Face and Megatron model definitions and checkpoints, along with robust, performant recipes built with Megatron Core for pretraining and fine-tuning large language models. It delivers state-of-the-art training throughput with advanced parallelism strategies and mixed precision support optimized for maximum performance at scale.

[NeMo RL](https://docs.nvidia.com/nemo/rl/latest/index.html.md) is a scalable and efficient post-training library designed for models ranging from 1 GPU to thousands, and from tiny to over 100 billion parameters.

What you can expect:

*   **Seamless integration with Hugging Face** for ease of use, allowing users to leverage a wide range of pre-trained models and tools.

*   **High-performance implementation with Megatron Core**, supporting various parallelism techniques for large models (>100B) and large context lengths.

*   **Efficient resource management using Ray**, enabling scalable and flexible deployment across different hardware configurations.

*   **Flexibility** with a modular design that allows easy integration and customization.

*   **Comprehensive documentation** that is both detailed and user-friendly, with practical examples.

[NeMo Run](https://docs.nvidia.com/nemo/run/latest/index.html.md) is a powerful tool designed to streamline the configuration, execution and management of Machine Learning experiments across various computing environments.

Links/Buttons:
- [#](https://docs.nvidia.com/nemo-framework/user-guide/latest/libraries/index.html.md#library-documentation)
- [NeMo](https://docs.nvidia.com/nemo-framework/user-guide/latest/nemotoolkit/index.html.md)
- [NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/latest/index.html)
- [NeMo Curator](https://docs.nvidia.com/nemo/curator/latest/index.html.md)
- [NeMo Eval](https://docs.nvidia.com/nemo/evaluator/latest/index.html.md)
- [NeMo Export and Deploy](https://docs.nvidia.com/nemo/export-deploy/latest/index.html.md)
- [NeMo Megatron Bridge](https://docs.nvidia.com/nemo/megatron-bridge/latest/index.html.md)
- [NeMo RL](https://docs.nvidia.com/nemo/rl/latest/index.html.md)
- [NeMo Run](https://docs.nvidia.com/nemo/run/latest/index.html.md)