End of training
Browse files- README.md +21 -0
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- checkpoint-100/pytorch_lora_weights.bin +3 -0
- checkpoint-100/random_states_0.pkl +3 -0
- checkpoint-100/scheduler.bin +3 -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-300/optimizer.bin +3 -0
- checkpoint-300/pytorch_lora_weights.bin +3 -0
- checkpoint-300/random_states_0.pkl +3 -0
- checkpoint-300/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-500/optimizer.bin +3 -0
- checkpoint-500/pytorch_lora_weights.bin +3 -0
- checkpoint-500/random_states_0.pkl +3 -0
- checkpoint-500/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-700/optimizer.bin +3 -0
- checkpoint-700/pytorch_lora_weights.bin +3 -0
- checkpoint-700/random_states_0.pkl +3 -0
- checkpoint-700/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
- checkpoint-900/optimizer.bin +3 -0
- checkpoint-900/pytorch_lora_weights.bin +3 -0
- checkpoint-900/random_states_0.pkl +3 -0
- checkpoint-900/scheduler.bin +3 -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: runwayml/stable-diffusion-v1-5
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instance_prompt: A house in 3d rendering 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 - Hekenye/3d
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These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on A house in 3d rendering 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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