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.github/workflows/example_tests.yml

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image: nvcr.io/nvidia/tensorrt-llm/release:1.1.0rc2.post2
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env:
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PIP_CONSTRAINT: "" # Disable pip constraint for upgrading packages
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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steps: &example_steps
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- uses: actions/checkout@v4
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- uses: nv-gha-runners/setup-proxy-cache@main

README.md

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______________________________________________________________________
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The **NVIDIA TensorRT Model Optimizer** (referred to as **Model Optimizer**, or **ModelOpt**) is a library comprising state-of-the-art model optimization [techniques](#techniques) including quantization, distillation, pruning, speculative decoding and sparsity to accelerate models.
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**NVIDIA TensorRT Model Optimizer** (referred to as **Model Optimizer**, or **ModelOpt**) is a library comprising state-of-the-art model optimization [techniques](#techniques) including quantization, distillation, pruning, speculative decoding and sparsity to accelerate models.
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**[Input]** Model Optimizer currently supports inputs of a [Hugging Face](https://huggingface.co/), [PyTorch](https://github.com/pytorch/pytorch) or [ONNX](https://github.com/onnx/onnx) model.
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