End of training
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- .ipynb_checkpoints/README-checkpoint.md +48 -0
- .ipynb_checkpoints/image_0-checkpoint.png +3 -0
- .ipynb_checkpoints/image_1-checkpoint.png +3 -0
- .ipynb_checkpoints/image_2-checkpoint.png +0 -0
- .ipynb_checkpoints/image_3-checkpoint.png +3 -0
- README.md +6 -0
- image_0.png +2 -2
- image_1.png +2 -2
- image_2.png +0 -0
- image_3.png +2 -2
- pytorch_lora_weights.safetensors +1 -1
.gitattributes
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.ipynb_checkpoints/README-checkpoint.md
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---
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base_model: stabilityai/stable-diffusion-xl-base-1.0
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library_name: diffusers
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license: creativeml-openrail-m
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tags:
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- stable-diffusion-xl
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- stable-diffusion-xl-diffusers
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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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<!-- This model card has been generated automatically according to the information the training script had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# LoRA text2image fine-tuning - bernice1/sd-naruto-model-lora-sdxl
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These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were fine-tuned on the birme 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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LoRA for the text encoder was enabled: False.
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Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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## Intended uses & limitations
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#### How to use
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```python
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# TODO: add an example code snippet for running this diffusion pipeline
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```
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#### Limitations and bias
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[TODO: provide examples of latent issues and potential remediations]
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## Training details
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[TODO: describe the data used to train the model]
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README.md
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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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- diffusers
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- diffusers-training
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- lora
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- stable-diffusion-xl
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- stable-diffusion-xl-diffusers
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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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pytorch_lora_weights.safetensors
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size 23390424
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