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  1. README.md +43 -0
  2. feature_extractor/preprocessor_config.json +27 -0
  3. logs/dreambooth/1739515955.7778652/events.out.tfevents.1739515955.4090-algo-3.3815673.1 +3 -0
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README.md ADDED
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1
+ ---
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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: a photo of sks dog
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+ tags:
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+ - text-to-image
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+ - dreambooth
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+ - diffusers-training
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+ - stable-diffusion
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+ - stable-diffusion-diffusers
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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
16
+ should probably proofread and complete it, then remove this comment. -->
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+
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+
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+ # DreamBooth - jingwufang/path-to-save-model
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+
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+ This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks dog using [DreamBooth](https://dreambooth.github.io/).
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+ 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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+ DreamBooth for the text encoder was enabled: False.
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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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+ {
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+ "width": 224
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+ },
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+ "do_center_crop": true,
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+ "do_convert_rgb": true,
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+ "do_normalize": true,
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+ "do_rescale": true,
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+ "do_resize": true,
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+ "image_mean": [
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+ 0.48145466,
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+ 0.4578275,
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+ 0.40821073
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+ ],
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+ "image_processor_type": "CLIPImageProcessor",
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+ "image_std": [
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+ 0.26862954,
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+ 0.26130258,
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+ 0.27577711
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+ ],
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+ "resample": 3,
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+ "rescale_factor": 0.00392156862745098,
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+ "size": {
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+ "shortest_edge": 224
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+ }
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+ }
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+ adam_beta1: 0.9
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+ adam_beta2: 0.999
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+ adam_epsilon: 1.0e-08
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+ adam_weight_decay: 0.01
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+ allow_tf32: false
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