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End of training
Browse files- README.md +18 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-500/optimizer.bin +3 -0
- checkpoint-500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-500/random_states_0.pkl +3 -0
- checkpoint-500/scaler.pt +3 -0
- checkpoint-500/scheduler.bin +3 -0
- image_0.png +0 -0
- pytorch_lora_weights.safetensors +3 -0
README.md
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---
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license: creativeml-openrail-m
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base_model: kandinsky-community/kandinsky-2-2-decoder
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tags:
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- kandinsky
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- text-to-image
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- diffusers
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- diffusers-training
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- lora
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inference: true
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---
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# LoRA text2image fine-tuning - SimonJonsson1999/test_lora_decoder
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These are LoRA adaption weights for kandinsky-community/kandinsky-2-2-decoder. The weights were fine-tuned on the None dataset. You can find some example images in the following.
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![img_0](./image_0.png)
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checkpoint-1000/optimizer.bin
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checkpoint-1000/pytorch_lora_weights.safetensors
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checkpoint-1000/random_states_0.pkl
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checkpoint-1000/scaler.pt
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checkpoint-1000/scheduler.bin
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checkpoint-500/optimizer.bin
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checkpoint-500/pytorch_lora_weights.safetensors
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checkpoint-500/random_states_0.pkl
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checkpoint-500/scaler.pt
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checkpoint-500/scheduler.bin
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image_0.png
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pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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size 3314280
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