lovelyjaban
commited on
End of training
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- .gitattributes +2 -0
- README.md +72 -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-10000/optimizer.bin +3 -0
- checkpoint-10000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-10000/random_states_0.pkl +3 -0
- checkpoint-10000/scaler.pt +3 -0
- checkpoint-10000/scheduler.bin +3 -0
- checkpoint-100000/optimizer.bin +3 -0
- checkpoint-100000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-100000/random_states_0.pkl +3 -0
- checkpoint-100000/scaler.pt +3 -0
- checkpoint-100000/scheduler.bin +3 -0
- checkpoint-100500/optimizer.bin +3 -0
- checkpoint-100500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-100500/random_states_0.pkl +3 -0
- checkpoint-100500/scaler.pt +3 -0
- checkpoint-100500/scheduler.bin +3 -0
- checkpoint-101000/optimizer.bin +3 -0
- checkpoint-101000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-101000/random_states_0.pkl +3 -0
- checkpoint-101000/scaler.pt +3 -0
- checkpoint-101000/scheduler.bin +3 -0
- checkpoint-101500/optimizer.bin +3 -0
- checkpoint-101500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-101500/random_states_0.pkl +3 -0
- checkpoint-101500/scaler.pt +3 -0
- checkpoint-101500/scheduler.bin +3 -0
- checkpoint-102000/optimizer.bin +3 -0
- checkpoint-102000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-102000/random_states_0.pkl +3 -0
- checkpoint-102000/scaler.pt +3 -0
- checkpoint-102000/scheduler.bin +3 -0
- checkpoint-102500/optimizer.bin +3 -0
- checkpoint-102500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-102500/random_states_0.pkl +3 -0
- checkpoint-102500/scaler.pt +3 -0
- checkpoint-102500/scheduler.bin +3 -0
- checkpoint-103000/optimizer.bin +3 -0
- checkpoint-103000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-103000/random_states_0.pkl +3 -0
- checkpoint-103000/scaler.pt +3 -0
- checkpoint-103000/scheduler.bin +3 -0
- checkpoint-103500/optimizer.bin +3 -0
- checkpoint-103500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-103500/random_states_0.pkl +3 -0
.gitattributes
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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zip 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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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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- lora
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- sd3
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- sd3-diffusers
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- template:sd-lora
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instance_prompt: hmwrks drawing style
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widget:
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- text: A photo of a t-shirt with hmwrks drawing style
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output:
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url: image_0.png
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- text: A photo of a t-shirt with hmwrks drawing style
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output:
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url: image_1.png
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- text: A photo of a t-shirt with hmwrks drawing style
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output:
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url: image_2.png
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- text: A photo of a t-shirt with hmwrks drawing style
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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 - lovelyjaban/trained-sd3-lora-test2
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<Gallery />
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## Model description
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These are lovelyjaban/trained-sd3-lora-test2 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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LoRA for the text encoder was enabled: False.
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## Trigger words
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You should use hmwrks drawing style to trigger the image generation.
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## Download model
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[Download](lovelyjaban/trained-sd3-lora-test2/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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