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Oedon42
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thangka-lora-xl

Text-to-Image
Diffusers
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
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  1. README.md +39 -0
  2. checkpoint-1000/optimizer.bin +3 -0
  3. checkpoint-1000/pytorch_lora_weights.safetensors +3 -0
  4. checkpoint-1000/random_states_0.pkl +3 -0
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  18. checkpoint-11500/optimizer.bin +3 -0
  19. checkpoint-11500/pytorch_lora_weights.safetensors +3 -0
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  22. checkpoint-12000/optimizer.bin +3 -0
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  28. checkpoint-12500/random_states_0.pkl +3 -0
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  30. checkpoint-13000/optimizer.bin +3 -0
  31. checkpoint-13000/pytorch_lora_weights.safetensors +3 -0
  32. checkpoint-13000/random_states_0.pkl +3 -0
  33. checkpoint-13000/scheduler.bin +3 -0
  34. checkpoint-13500/optimizer.bin +3 -0
  35. checkpoint-13500/pytorch_lora_weights.safetensors +3 -0
  36. checkpoint-13500/random_states_0.pkl +3 -0
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  40. checkpoint-14000/random_states_0.pkl +3 -0
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  42. checkpoint-14500/optimizer.bin +3 -0
  43. checkpoint-14500/pytorch_lora_weights.safetensors +3 -0
  44. checkpoint-14500/random_states_0.pkl +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: 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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+ inference: true
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+ tags:
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+ - stable-diffusion
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+ - stable-diffusion-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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+ ---
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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 - Oedon42/thangka-lora-xl
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+ These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were fine-tuned on the Oedon42/Thang-ka dataset. 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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+ ## 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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