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Getting Started

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  • Installation
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      • Install ModelOpt-Windows as a Standalone Toolkit
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  • Quick Start: PTQ - PyTorch
  • Quick Start: PTQ - ONNX
  • Quick Start: PTQ - PyTorch to ONNX
  • Quick Start: PTQ - Windows
  • Quick Start: QAT
  • Quick Start: Pruning
  • Quick Start: Distillation
  • Quick Start: Speculative Decoding
  • Quick Start: Sparsity

Guides

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  • Quantization
    • Basic Concepts
    • Best practices to choose the right quantization methods
    • PyTorch Quantization
    • Quantization Configuration (quant_cfg)
    • Guides to quantize a customized model from Hugging Face for TensorRT-LLM deployment
    • Compress quantized models
    • ONNX Quantization - Linux (Beta)
    • ONNX Quantization - Windows
  • Saving & Restoring
  • Pruning
  • Distillation
  • Speculative Decoding
  • Sparsity
  • NAS
  • AutoCast (ONNX)
  • Autotune (ONNX)

Deployment

  • TensorRT-LLM
  • Onnxruntime
  • Unified HuggingFace Checkpoint

Examples

  • All GitHub Examples

Reference

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  1. Model Optimizer /
  2. modelopt API /
  3. torch /
  4. puzzletron /
  5. dataset

dataset#

Modules

modelopt.torch.puzzletron.dataset.prepare_dataset

Dataset preparation utilities for Puzzletron.

Previous
build_library_and_stats
Next
prepare_dataset

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