agentmods.dev

NVIDIA/Model-Optimizer

A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.

About the project

NVIDIA Model Optimizer is a library that changes deep-learning models through techniques such as quantization, pruning, distillation, neural architecture search, speculative decoding, and sparsity so they can run more efficiently. Developers use it to optimize Hugging Face, PyTorch, or ONNX models and export checkpoints for inference frameworks such as SGLang, TensorRT-LLM, TensorRT, or vLLM. The catalogue entries provide skills, instructions, and a plugin for using its workflows.

This repository also configures its own agents. See what Model-Optimizer tells them →

Open on GitHub nvidia.github.io
5.4kStars on the repository
24Mods indexed here, across every type
todayLast push, which is what freshness is scored on
Apache-2.0Licence, which decides whether bodies are shown
Sort RelevanceRecently updatedFewest tokensSecurity gradeRepo starsStars this weekTop rated 5 mods

At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: