eristotelian
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- README.md +17 -0
- checkpoint-100/custom_checkpoint_0.pkl +3 -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/custom_checkpoint_0.pkl +3 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_model.bin +3 -0
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- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-200/custom_checkpoint_0.pkl +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-300/custom_checkpoint_0.pkl +3 -0
- checkpoint-300/optimizer.bin +3 -0
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- checkpoint-300/scaler.pt +3 -0
- checkpoint-300/scheduler.bin +3 -0
- checkpoint-400/custom_checkpoint_0.pkl +3 -0
- checkpoint-400/optimizer.bin +3 -0
- checkpoint-400/pytorch_model.bin +3 -0
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- checkpoint-400/scaler.pt +3 -0
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- checkpoint-700/scaler.pt +3 -0
- checkpoint-700/scheduler.bin +3 -0
- checkpoint-800/custom_checkpoint_0.pkl +3 -0
README.md
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---
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license: creativeml-openrail-m
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base_model: CompVis/stable-diffusion-v1-4
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instance_prompt: simlora
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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 DreamBooth - simlora
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These are LoRA adaption weights for [CompVis/stable-diffusion-v1-4](https://huggingface.co/CompVis/stable-diffusion-v1-4). The weights were trained on the instance prompt "simlora" using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following.
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checkpoint-700/pytorch_model.bin
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checkpoint-700/random_states_0.pkl
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checkpoint-700/scaler.pt
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version https://git-lfs.github.com/spec/v1
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checkpoint-700/scheduler.bin
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checkpoint-800/custom_checkpoint_0.pkl
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