End of training
Browse files- README.md +25 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_lora_weights.bin +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-200/optimizer.bin +3 -0
- checkpoint-200/pytorch_lora_weights.bin +3 -0
- checkpoint-200/random_states_0.pkl +3 -0
- checkpoint-200/scheduler.bin +3 -0
- checkpoint-400/optimizer.bin +3 -0
- checkpoint-400/pytorch_lora_weights.bin +3 -0
- checkpoint-400/random_states_0.pkl +3 -0
- checkpoint-400/scheduler.bin +3 -0
- checkpoint-600/optimizer.bin +3 -0
- checkpoint-600/pytorch_lora_weights.bin +3 -0
- checkpoint-600/random_states_0.pkl +3 -0
- checkpoint-600/scheduler.bin +3 -0
- checkpoint-800/optimizer.bin +3 -0
- checkpoint-800/pytorch_lora_weights.bin +3 -0
- checkpoint-800/random_states_0.pkl +3 -0
- checkpoint-800/scheduler.bin +3 -0
- image_0.png +0 -0
- image_1.png +0 -0
- image_2.png +0 -0
- image_3.png +0 -0
- pytorch_lora_weights.bin +3 -0
README.md
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---
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license: creativeml-openrail-m
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base_model: envvi/inkpunk-diffusion
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instance_prompt: a photo in vinpo style
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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 - ephmecx/vinpo-inkpunk
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These are LoRA adaption weights for envvi/inkpunk-diffusion. The weights were trained on a photo in vinpo style using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following.
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LoRA for the text encoder was enabled: False.
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