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| | license: mit |
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| | [](https://discord.gg/2JhHVh7CGu) |
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| | A semi custom network based on the follow paper [Simpler Diffusion (SiD2)](https://arxiv.org/abs/2410.19324v1) |
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| | This network uses the optimal transport flow matching objective outlined [Flow Matching for Generative Modeling](https://arxiv.org/abs/2210.02747) |
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| | xATGLU Layers are used instead of linears for entry into the transformer MLP layer [Expanded Gating Ranges |
| | Improve Activation Functions](https://arxiv.org/pdf/2405.20768) |
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| | `python train.py` will train a new image network on the provided dataset. A pretrained model is provided here, step_1799.safetensors. To test, use: |
| | `python test_sample.py step_1799.safetensors` |
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