End of training
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- .gitattributes +3 -0
- README.md +19 -1
- checkpoint-10000/optimizer.bin +3 -0
- checkpoint-10000/pytorch_model.bin +3 -0
- checkpoint-10000/random_states_0.pkl +3 -0
- checkpoint-10000/scaler.pt +3 -0
- checkpoint-10000/scheduler.bin +3 -0
- checkpoint-100000/optimizer.bin +3 -0
- checkpoint-100000/pytorch_model.bin +3 -0
- checkpoint-100000/random_states_0.pkl +3 -0
- checkpoint-100000/scaler.pt +3 -0
- checkpoint-100000/scheduler.bin +3 -0
- checkpoint-105000/optimizer.bin +3 -0
- checkpoint-105000/pytorch_model.bin +3 -0
- checkpoint-105000/random_states_0.pkl +3 -0
- checkpoint-105000/scaler.pt +3 -0
- checkpoint-105000/scheduler.bin +3 -0
- checkpoint-110000/optimizer.bin +3 -0
- checkpoint-110000/pytorch_model.bin +3 -0
- checkpoint-110000/random_states_0.pkl +3 -0
- checkpoint-110000/scaler.pt +3 -0
- checkpoint-110000/scheduler.bin +3 -0
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- checkpoint-115000/pytorch_model.bin +3 -0
- checkpoint-115000/random_states_0.pkl +3 -0
- checkpoint-115000/scaler.pt +3 -0
- checkpoint-115000/scheduler.bin +3 -0
- checkpoint-120000/optimizer.bin +3 -0
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- checkpoint-120000/random_states_0.pkl +3 -0
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- checkpoint-125000/scheduler.bin +3 -0
- checkpoint-130000/optimizer.bin +3 -0
- checkpoint-130000/pytorch_model.bin +3 -0
- checkpoint-130000/random_states_0.pkl +3 -0
- checkpoint-130000/scaler.pt +3 -0
- checkpoint-130000/scheduler.bin +3 -0
- checkpoint-135000/optimizer.bin +3 -0
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- checkpoint-135000/scheduler.bin +3 -0
- checkpoint-140000/optimizer.bin +3 -0
- checkpoint-140000/pytorch_model.bin +3 -0
- checkpoint-140000/random_states_0.pkl +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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-
license:
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---
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---
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license: creativeml-openrail-m
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base_model: stabilityai/stable-diffusion-2
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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 - mozci/typestablediff
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These are LoRA adaption weights for stabilityai/stable-diffusion-2. The weights were fine-tuned on the mozci/typedb 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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