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README.md
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@@ -19,6 +19,13 @@ These are comparion for this model ran on T4 GPU, compared with segmind/tiny-sd,
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### THIS IS NOT THE FULL DESCRIPTION FOR THIS MODEL.
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3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
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[Please read the full license here](https://huggingface.co/spaces/CompVis/stable-diffusion-license)
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```python
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import torch
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from diffusers import StableDiffusionPipeline
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# Training info
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Learning rate: 5e-5 (0.00005) <br>
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Batch size: 8 <br>
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Number of steps: 1000 <br>
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Training methond: Knowledge Distillation <br>
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Trained on: x1 T4 GPU <br>
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### THIS IS NOT THE FULL DESCRIPTION FOR THIS MODEL.
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3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
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[Please read the full license here](https://huggingface.co/spaces/CompVis/stable-diffusion-license)
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# Example coe:
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```python
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import torch
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from diffusers import StableDiffusionPipeline
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