End of training
Browse files- .gitattributes +1 -0
- README.md +69 -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
- image_1.png +0 -0
- image_2.png +3 -0
- image_3.png +0 -0
- pytorch_lora_weights.safetensors +3 -0
.gitattributes
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*.zst 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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- diffusers-training
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- diffusers
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- sd3
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- sd3-diffusers
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- template:sd-lora
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base_model: stabilityai/stable-diffusion-3-medium-diffusers
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instance_prompt: model is wearing
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widget:
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- text: model is wearing
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output:
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url: image_0.png
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- text: model is wearing
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output:
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url: image_1.png
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- text: model is wearing
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output:
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url: image_2.png
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- text: model is wearing
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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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# SD3 DreamBooth LoRA - kadirnar/vton_mini
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<Gallery />
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## Model description
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These are kadirnar/vton_mini DreamBooth weights for stabilityai/stable-diffusion-3-medium-diffusers.
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The weights were trained using [DreamBooth](https://dreambooth.github.io/).
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## Trigger words
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You should use model is wearing to trigger the image generation.
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## Download model
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[Download](kadirnar/vton_mini/tree/main) them in the Files & versions tab.
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## License
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Please adhere to the licensing terms as described `[here](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE)`.
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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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image_0.png
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image_1.png
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image_2.png
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pytorch_lora_weights.safetensors
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