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  1. README.md +48 -0
  2. checkpoint-14500/optimizer.bin +3 -0
  3. checkpoint-14500/pytorch_lora_weights.safetensors +3 -0
  4. checkpoint-14500/random_states_0.pkl +3 -0
  5. checkpoint-14500/scaler.pt +3 -0
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  7. checkpoint-15000/optimizer.bin +3 -0
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  13. image_1.png +0 -0
  14. image_2.png +0 -0
  15. image_3.png +0 -0
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  27. logs/text2image-fine-tune/1721612483.0174372/hparams.yml +54 -0
  28. logs/text2image-fine-tune/events.out.tfevents.1721576160.autodl-container-db4a40b195-60ebac9c.1142.0 +3 -0
  29. logs/text2image-fine-tune/events.out.tfevents.1721577391.autodl-container-db4a40b195-60ebac9c.1839.0 +3 -0
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  32. logs/text2image-fine-tune/events.out.tfevents.1721578123.autodl-container-db4a40b195-60ebac9c.4005.0 +3 -0
  33. logs/text2image-fine-tune/events.out.tfevents.1721612483.autodl-container-db4a40b195-60ebac9c.1182.0 +3 -0
  34. pytorch_lora_weights.safetensors +3 -0
README.md ADDED
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+ ---
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+ base_model: stabilityai/stable-diffusion-xl-base-1.0
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+ library_name: diffusers
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+ license: creativeml-openrail-m
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+ tags:
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+ - stable-diffusion-xl
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+ - stable-diffusion-xl-diffusers
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+ - text-to-image
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+ - diffusers
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+ - diffusers-training
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+ - lora
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+ inference: true
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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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+ # LoRA text2image fine-tuning - spockren/naruto-lora-xl
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+
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+ These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were fine-tuned on the lambdalabs/naruto-blip-captions dataset. You can find some example images in the following.
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+
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+ ![img_0](./image_0.png)
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+ ![img_1](./image_1.png)
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+ ![img_2](./image_2.png)
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+ ![img_3](./image_3.png)
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+
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+
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+ LoRA for the text encoder was enabled: False.
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+
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+ Special VAE used for training: None.
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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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