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End of training

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.gitattributes CHANGED
@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ ---
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+ base_model: stabilityai/stable-diffusion-3-medium-diffusers
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+ library_name: diffusers
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+ license: openrail++
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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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+ instance_prompt: a photo of sks dog
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+ widget:
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+ - text: A photo of sks dog in a bucket
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+ output:
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+ url: image_0.png
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+ - text: A photo of sks dog in a bucket
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+ output:
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+ url: image_1.png
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+ - text: A photo of sks dog in a bucket
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+ output:
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+ url: image_2.png
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+ - text: A photo of sks dog in a bucket
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+ output:
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+ url: image_3.png
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+ ---
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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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+
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+
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+ # SD3 DreamBooth - feiyangyang/trained-sd3
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+
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+ <Gallery />
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+
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+ ## Model description
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+
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+ These are feiyangyang/trained-sd3 DreamBooth weights for stabilityai/stable-diffusion-3-medium-diffusers.
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+
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+ The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sd3.md).
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+
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+ Was the text encoder fine-tuned? False.
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+
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+ ## Trigger words
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+
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+ You should use `a photo of sks dog` to trigger the image generation.
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+
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+ ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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+
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+ ```py
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+ from diffusers import AutoPipelineForText2Image
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+ import torch
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+ pipeline = AutoPipelineForText2Image.from_pretrained('feiyangyang/trained-sd3', torch_dtype=torch.float16).to('cuda')
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+ image = pipeline('A photo of sks dog in a bucket').images[0]
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+ ```
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+
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+ ## License
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+
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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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+
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+
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+ ## Intended uses & limitations
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+
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+ #### How to use
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+
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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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+
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+ #### Limitations and bias
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+
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+ [TODO: provide examples of latent issues and potential remediations]
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+
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+ ## Training details
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+
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+ [TODO: describe the data used to train the model]
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