Inferenza, distribuzione e runtime

Model-Optimizer

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.

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⑂ 513Fork
318Problemi aperti
PythonLingua
Apache-2.0Licenza
Q@project.QualityScorePunteggio editoriale

Panoramica

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.

Requisiti, installazione e avvio rapido

I requisiti di installazione non sono indicati nei metadati del repository.

Utilizzo

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Compatibilità del modello e casi d'uso

La compatibilità del modello non è indicata nei metadati del repository.

Note su licenza e rischi

Apache-2.0

ToolAI metadata-only listing: repository metadata is public; editorial content and manual verification are still pending. Quality score was recomputed from live GitHub repository facts on 2026-08-22 UTC using the seven-dimension channel formula.

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