End of training
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- .gitattributes +4 -0
- README.md +84 -0
- checkpoint-1200/optimizer.bin +3 -0
- checkpoint-1200/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1200/random_states_0.pkl +3 -0
- checkpoint-1200/scheduler.bin +3 -0
- checkpoint-1800/optimizer.bin +3 -0
- checkpoint-1800/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1800/random_states_0.pkl +3 -0
- checkpoint-1800/scheduler.bin +3 -0
- checkpoint-2400/optimizer.bin +3 -0
- checkpoint-2400/pytorch_lora_weights.safetensors +3 -0
- checkpoint-2400/random_states_0.pkl +3 -0
- checkpoint-2400/scheduler.bin +3 -0
- checkpoint-3000/optimizer.bin +3 -0
- checkpoint-3000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-3000/random_states_0.pkl +3 -0
- checkpoint-3000/scheduler.bin +3 -0
- checkpoint-3600/optimizer.bin +3 -0
- checkpoint-3600/pytorch_lora_weights.safetensors +3 -0
- checkpoint-3600/random_states_0.pkl +3 -0
- checkpoint-3600/scheduler.bin +3 -0
- checkpoint-4200/optimizer.bin +3 -0
- checkpoint-4200/pytorch_lora_weights.safetensors +3 -0
- checkpoint-4200/random_states_0.pkl +3 -0
- checkpoint-4200/scheduler.bin +3 -0
- checkpoint-4800/optimizer.bin +3 -0
- checkpoint-4800/pytorch_lora_weights.safetensors +3 -0
- checkpoint-4800/random_states_0.pkl +3 -0
- checkpoint-4800/scheduler.bin +3 -0
- checkpoint-5400/optimizer.bin +3 -0
- checkpoint-5400/pytorch_lora_weights.safetensors +3 -0
- checkpoint-5400/random_states_0.pkl +3 -0
- checkpoint-5400/scheduler.bin +3 -0
- checkpoint-600/optimizer.bin +3 -0
- checkpoint-600/pytorch_lora_weights.safetensors +3 -0
- checkpoint-600/random_states_0.pkl +3 -0
- checkpoint-600/scheduler.bin +3 -0
- checkpoint-6000/optimizer.bin +3 -0
- checkpoint-6000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-6000/random_states_0.pkl +3 -0
- checkpoint-6000/scheduler.bin +3 -0
- checkpoint-900/optimizer.bin +3 -0
- checkpoint-900/pytorch_lora_weights.safetensors +3 -0
- checkpoint-900/random_states_0.pkl +3 -0
- checkpoint-900/scheduler.bin +3 -0
- image_0.png +3 -0
- image_1.png +3 -0
- image_2.png +3 -0
- image_3.png +3 -0
.gitattributes
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@@ -33,3 +33,7 @@ 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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*.zst filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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base_model: black-forest-labs/FLUX.1-Fill-dev
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library_name: diffusers
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license: other
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instance_prompt: Hadshdw object, hard gray shadow on the bottom, pure white background
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widget:
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- text: Hadshdw object, hard gray shadow on the bottom, pure white background
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output:
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url: image_0.png
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- text: Hadshdw object, hard gray shadow on the bottom, pure white background
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output:
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url: image_1.png
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- text: Hadshdw object, hard gray shadow on the bottom, pure white background
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output:
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url: image_2.png
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- text: Hadshdw object, hard gray shadow on the bottom, pure white background
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output:
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url: image_3.png
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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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- flux
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- flux-diffusers
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- template:sd-lora
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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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# Flux-Fill DreamBooth LoRA - cucucu666/flux_hard_4.22
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<Gallery />
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## Model description
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These are cucucu666/flux_hard_4.22 DreamBooth LoRA weights for black-forest-labs/FLUX.1-Fill-dev.
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The weights were trained using [DreamBooth](https://dreambooth.github.io/) with a custom [Flux diffusers trainer](https://github.com/Sebastian-Zok/FLUX-Fill-LoRa-Training).
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Was LoRA for the text encoder enabled? False.
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## Trigger words
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You should use `Hadshdw object, hard gray shadow on the bottom, pure white background` to trigger the image generation.
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## Download model
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[Download the *.safetensors LoRA](cucucu666/flux_hard_4.22/tree/main) in the Files & versions tab.
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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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("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to('cuda')
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pipeline.load_lora_weights('cucucu666/flux_hard_4.22', weight_name='pytorch_lora_weights.safetensors')
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image = pipeline('Hadshdw object, hard gray shadow on the bottom, pure white background').images[0]
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```
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For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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## License
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Please adhere to the licensing terms as described [here](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md).
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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
ADDED
![]() |
Git LFS Details
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image_1.png
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![]() |
Git LFS Details
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image_2.png
ADDED
![]() |
Git LFS Details
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image_3.png
ADDED
![]() |
Git LFS Details
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