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README.md
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---
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<div align="center">
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#
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Anonymous source-code repository.
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[Model checkpoints](https://huggingface.co/Elastic-forcing/
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[1.3B Training & Inference](1.3B/README.md) · [14B Training & Inference](14B/README.md)
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The 1.3B three-encoder configuration achieves **84.25 VBench Total** in the paper. The 14B release targets the **step-80 checkpoint**, retaining the first 80 updates of the original **200-step cosine learning-rate schedule**. This is the **three-encoder, 8,000-reference-video model used in the human and VLM evaluations**; see [evaluated settings](14B/docs/evaluated-settings.md).
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```text
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├── 1.3B/ # Three-encoder training and inference
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│ ├── code/
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│ ├── configs/
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## Getting Started
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```bash
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git clone https://huggingface.co/Elastic-forcing/
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cd
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# Choose one model, then follow its README.
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cd 14B
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---
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<div align="center">
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# Elastic-forcing-code
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Anonymous source-code repository.
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[Model checkpoints](https://huggingface.co/Elastic-forcing/Elastic-forcing-checkpoint)
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[1.3B Training & Inference](1.3B/README.md) · [14B Training & Inference](14B/README.md)
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The 1.3B three-encoder configuration achieves **84.25 VBench Total** in the paper. The 14B release targets the **step-80 checkpoint**, retaining the first 80 updates of the original **200-step cosine learning-rate schedule**. This is the **three-encoder, 8,000-reference-video model used in the human and VLM evaluations**; see [evaluated settings](14B/docs/evaluated-settings.md).
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```text
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Elastic-forcing-code/
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├── 1.3B/ # Three-encoder training and inference
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│ ├── code/
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│ ├── configs/
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## Getting Started
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```bash
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git clone https://huggingface.co/Elastic-forcing/Elastic-forcing-code
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cd Elastic-forcing-code
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# Choose one model, then follow its README.
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cd 14B
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