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End of training

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  1. <new1>.safetensors +3 -0
  2. README.md +44 -0
  3. checkpoint-1000/custom_checkpoint_0.pkl +3 -0
  4. checkpoint-1000/model.safetensors +3 -0
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  27. logs/custom-diffusion/1734795754.6958354/events.out.tfevents.1734795754.80baea66d89d.18439.1 +3 -0
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  29. logs/custom-diffusion/1734796711.277155/events.out.tfevents.1734796711.80baea66d89d.22590.1 +3 -0
  30. logs/custom-diffusion/1734796711.2788737/hparams.yml +57 -0
  31. logs/custom-diffusion/1734796797.880242/events.out.tfevents.1734796797.80baea66d89d.23038.1 +3 -0
  32. logs/custom-diffusion/1734796797.8819876/hparams.yml +57 -0
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  37. logs/custom-diffusion/events.out.tfevents.1734796797.80baea66d89d.23038.0 +3 -0
  38. logs/custom-diffusion/events.out.tfevents.1734797982.80baea66d89d.31751.0 +3 -0
  39. pytorch_custom_diffusion_weights.safetensors +3 -0
<new1>.safetensors ADDED
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+ ---
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+ base_model: CompVis/stable-diffusion-v1-4
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+ library_name: diffusers
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+ license: creativeml-openrail-m
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+ inference: true
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+ instance_prompt: photo of the <new1> style
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+ tags:
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+ - text-to-image
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+ - diffusers
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+ - stable-diffusion
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+ - stable-diffusion-diffusers
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+ - custom-diffusion
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+ - diffusers-training
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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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+ # Custom Diffusion - Andy9310/saved_model
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+
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+ These are Custom Diffusion adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on photo of the <new1> style using [Custom Diffusion](https://www.cs.cmu.edu/~custom-diffusion). You can find some example images in the following.
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+
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+
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+
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+
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+ For more details on the training, please follow [this link](https://github.com/huggingface/diffusers/blob/main/examples/custom_diffusion).
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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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