Model-Optimizer
A unified library of SOTA model optimization techniques.
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nvidia.github.io
About Model-Optimizer
Model-Optimizer is 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.
Description summarised by AI from the sources listed below.
Key features
- Quantization
- Distillation
- Pruning
- Neural Architecture Search
- Speculative Decoding
Use cases
- Deep learning model compression
- Inference speed optimization
Pricing
Pricing model: Open source. Detailed plans are not recorded; check the official website for current prices.
Pricing summarised by AI from the sources listed below.
