End of training
Browse files- .gitattributes +4 -0
- README.md +78 -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 +3 -0
- image_1.png +3 -0
- image_2.png +3 -0
- image_3.png +3 -0
- pytorch_lora_weights.safetensors +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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image_0.png filter=lfs diff=lfs merge=lfs -text
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image_1.png filter=lfs diff=lfs merge=lfs -text
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image_2.png filter=lfs diff=lfs merge=lfs -text
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image_3.png filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: openrail++
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library_name: diffusers
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tags:
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- text-to-image
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- text-to-image
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- diffusers-training
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- diffusers
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- lora
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- template:sd-lora
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- stable-diffusion-xl
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- stable-diffusion-xl-diffusers
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base_model: stabilityai/stable-diffusion-xl-base-1.0
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instance_prompt: a photo of Raclette cheese
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widget:
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- text: A close-up shot of a person dipping RACLETTE cheese into a warm, golden-brown
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pan.
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output:
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url: image_0.png
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- text: A close-up shot of a person dipping RACLETTE cheese into a warm, golden-brown
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pan.
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output:
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url: image_1.png
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- text: A close-up shot of a person dipping RACLETTE cheese into a warm, golden-brown
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pan.
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output:
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url: image_2.png
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- text: A close-up shot of a person dipping RACLETTE cheese into a warm, golden-brown
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pan.
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output:
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url: image_3.png
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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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# SDXL LoRA DreamBooth - JawadC/raclette
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<Gallery />
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## Model description
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These are JawadC/raclette LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
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The weights were trained using [DreamBooth](https://dreambooth.github.io/).
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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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## Trigger words
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You should use a photo of Raclette cheese to trigger the image generation.
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## Download model
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Weights for this model are available in Safetensors format.
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[Download](JawadC/raclette/tree/main) them in the Files & versions tab.
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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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checkpoint-500/optimizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:3bef4014c29f11a63be595accac12ee3969e535246f41f54f756bd932fef0ed7
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size 47392882
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checkpoint-500/pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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size 23390424
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checkpoint-500/random_states_0.pkl
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version https://git-lfs.github.com/spec/v1
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size 14280
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checkpoint-500/scaler.pt
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version https://git-lfs.github.com/spec/v1
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size 988
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checkpoint-500/scheduler.bin
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version https://git-lfs.github.com/spec/v1
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size 1000
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image_0.png
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Git LFS Details
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image_1.png
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Git LFS Details
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image_2.png
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Git LFS Details
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image_3.png
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Git LFS Details
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pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:db632287ec94c0d14a04e396ae4ecf02cb7131697549c8dfb340c33a48823512
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size 23390424
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