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Getting Started

  • Overview
  • Installation
    • Installation for Linux
    • Installation for Windows
      • Install ModelOpt-Windows as a Standalone Toolkit
      • Install ModelOpt-Windows with Olive
  • 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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  • ModelOpt Config System
  • 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

  • Changelog
  • modelopt API
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      • llm_export_utils
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        • surgeon_utils
      • logging_config
      • op_types
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        • autotune
        • calib_utils
        • extensions
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        • graph_utils
        • gs_patching
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        • speech_dataset_utils
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        • vlm_dataset_utils

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  7. qwen3

qwen3#

Modules

modelopt.torch.puzzletron.anymodel.models.qwen3.qwen3_converter

modelopt.torch.puzzletron.anymodel.models.qwen3.qwen3_model_descriptor

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