End of training
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- .gitattributes +1 -0
- README.md +21 -0
- checkpoint-100/optimizer.bin +3 -0
- checkpoint-100/pytorch_model.bin +3 -0
- checkpoint-100/random_states_0.pkl +3 -0
- checkpoint-100/scaler.pt +3 -0
- checkpoint-100/scheduler.bin +3 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_model.bin +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-150/optimizer.bin +3 -0
- checkpoint-150/pytorch_model.bin +3 -0
- checkpoint-150/random_states_0.pkl +3 -0
- checkpoint-150/scaler.pt +3 -0
- checkpoint-150/scheduler.bin +3 -0
- checkpoint-200/optimizer.bin +3 -0
- checkpoint-200/pytorch_model.bin +3 -0
- checkpoint-200/random_states_0.pkl +3 -0
- checkpoint-200/scaler.pt +3 -0
- checkpoint-200/scheduler.bin +3 -0
- checkpoint-250/optimizer.bin +3 -0
- checkpoint-250/pytorch_model.bin +3 -0
- checkpoint-250/random_states_0.pkl +3 -0
- checkpoint-250/scaler.pt +3 -0
- checkpoint-250/scheduler.bin +3 -0
- checkpoint-300/optimizer.bin +3 -0
- checkpoint-300/pytorch_model.bin +3 -0
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- checkpoint-300/scheduler.bin +3 -0
- checkpoint-350/optimizer.bin +3 -0
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- checkpoint-350/scheduler.bin +3 -0
- checkpoint-400/optimizer.bin +3 -0
- checkpoint-400/pytorch_model.bin +3 -0
- checkpoint-400/random_states_0.pkl +3 -0
- checkpoint-400/scaler.pt +3 -0
- checkpoint-400/scheduler.bin +3 -0
- checkpoint-450/optimizer.bin +3 -0
- checkpoint-450/pytorch_model.bin +3 -0
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- checkpoint-450/scheduler.bin +3 -0
- checkpoint-50/optimizer.bin +3 -0
- checkpoint-50/pytorch_model.bin +3 -0
- checkpoint-50/random_states_0.pkl +3 -0
.gitattributes
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@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: creativeml-openrail-m
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base_model: stabilityai/stable-diffusion-2-1
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- text-to-image
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- diffusers
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- lora
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inference: true
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---
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# LoRA text2image fine-tuning - Jiachang/pokemon-lora
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These are LoRA adaption weights for stabilityai/stable-diffusion-2-1. The weights were fine-tuned on the lambdalabs/pokemon-blip-captions dataset. You can find some example images in the following.
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![img_0](./image_0.png)
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![img_1](./image_1.png)
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![img_2](./image_2.png)
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![img_3](./image_3.png)
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