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.ci/ignore_treon_docker.txt

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notebooks/kokoro/kokoro.ipynb
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notebooks/qwen2.5-omni-chatbot/qwen2.5-omni-chatbot.ipynb
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notebooks/intern-video2-classiciation/intern-video2-classification.ipynb
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notebooks/flex.2-image-generation/flex.2-image-generation.ipynb
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notebooks/flex.2-image-generation/flex.2-image-generation.ipynb
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notebooks/wan2.1-text-to-video/wan2.1-text-to-video.ipynb

.ci/skipped_notebooks.yml

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skips:
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- os:
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- macos-13
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- notebook: notebooks/wan2.1-text-to-video/wan2.1-text-to-video.ipynb
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skips:
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- os:
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- macos-13
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- ubuntu-22.04
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- windows-2019

notebooks/wan2.1-text-to-video/README.md

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1. Student Initialization: Initialization of the causal student by pretraining it on a small set of ODE solution pairs generated by the bidirectional teacher. This step helps stabilize the subsequent distillation training.
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2. Asymmetric Distillation: Using the bidirectional teacher model, we train the causal student generator through a distribution matching distillation loss.
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More details about CausVid can be found in the [paper](https://arxiv.org/abs/2412.07772), [original repository](https://github.com/tianweiy/CausVi) and [project page](https://causvid.github.io/)
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More details about CausVid can be found in the [paper](https://arxiv.org/abs/2412.07772), [original repository](https://github.com/tianweiy/CausVid) and [project page](https://causvid.github.io/)
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## Notebook contents

notebooks/wan2.1-text-to-video/wan2.1-text-to-video.ipynb

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" 1. Student Initialization: Initialization of the causal student by pretraining it on a small set of ODE solution pairs generated by the bidirectional teacher. This step helps stabilize the subsequent distillation training.\n",
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" 2. Asymmetric Distillation: Using the bidirectional teacher model, we train the causal student generator through a distribution matching distillation loss. \n",
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"\n",
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"More details about CausVid can be found in the [paper](https://arxiv.org/abs/2412.07772), [original repository](https://github.com/tianweiy/CausVi) and [project page](https://causvid.github.io/)\n",
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"More details about CausVid can be found in the [paper](https://arxiv.org/abs/2412.07772), [original repository](https://github.com/tianweiy/CausVid) and [project page](https://causvid.github.io/)\n",
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"#### Table of contents:\n",
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"\n",
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"- [Prerequisites](#Prerequisites)\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"import platform\n",
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"\n",
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"%pip install -q \"torch>=2.1\" \"git+https://github.com/huggingface/diffusers.git\" \"transformers>=4.49.0\" \"accelerate\" \"safetensors\" \"sentencepiece\" \"peft>=0.7.0\" \"ftfy\" \"gradio>=4.19\" \"opencv-python\" --extra-index-url https://download.pytorch.org/whl/cpu\n",
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"%pip install --pre -U \"openvino>=2025.1.0\" \"nncf>=2.16.0\" --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/nightly"
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"%pip install --pre -U \"openvino>=2025.1.0\" \"nncf>=2.16.0\" --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/nightly\n",
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"\n",
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"if platform.system() == \"Darwin\":\n",
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" %pip install -q \"numpy<2.0.0\""
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]
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},
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{

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