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xgemstarx
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jm250_bs4

Text-to-Image
Diffusers
TensorBoard
diffusers-training
lora
flux
flux-diffusers
template:sd-lora
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  1. README.md +72 -0
  2. checkpoint-1000/optimizer.bin +3 -0
  3. checkpoint-1000/pytorch_lora_weights.safetensors +3 -0
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  46. checkpoint-1500/optimizer.bin +3 -0
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README.md ADDED
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+ ---
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+ base_model: black-forest-labs/FLUX.1-dev
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+ library_name: diffusers
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+ license: other
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+ instance_prompt: a photo of xjiminx
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+ widget: []
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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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+
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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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+ # Flux DreamBooth LoRA - xgemstarx/jm250_bs4
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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 xgemstarx/jm250_bs4 DreamBooth LoRA weights for black-forest-labs/FLUX.1-dev.
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+
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+ The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [Flux diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_flux.md).
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+
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+ Was LoRA for the text encoder enabled? 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 xjiminx` to trigger the image generation.
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+
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+ ## Download model
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+
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+ [Download the *.safetensors LoRA](xgemstarx/jm250_bs4/tree/main) in the Files & versions tab.
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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("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to('cuda')
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+ pipeline.load_lora_weights('xgemstarx/jm250_bs4', weight_name='pytorch_lora_weights.safetensors')
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+ image = pipeline('a photo of xjiminx').images[0]
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+ ```
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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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+
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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/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md).
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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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