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rayaanoidpr
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wongkarwai_LoRA

Text-to-Image
Diffusers
TensorBoard
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
template:sd-lora
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  1. README.md +64 -0
  2. checkpoint-100/optimizer.bin +3 -0
  3. checkpoint-100/pytorch_lora_weights.safetensors +3 -0
  4. checkpoint-100/random_states_0.pkl +3 -0
  5. checkpoint-100/scaler.pt +3 -0
  6. checkpoint-100/scheduler.bin +3 -0
  7. checkpoint-1000/optimizer.bin +3 -0
  8. checkpoint-1000/pytorch_lora_weights.safetensors +3 -0
  9. checkpoint-1000/random_states_0.pkl +3 -0
  10. checkpoint-1000/scaler.pt +3 -0
  11. checkpoint-1000/scheduler.bin +3 -0
  12. checkpoint-1100/optimizer.bin +3 -0
  13. checkpoint-1100/pytorch_lora_weights.safetensors +3 -0
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  15. checkpoint-1100/scaler.pt +3 -0
  16. checkpoint-1100/scheduler.bin +3 -0
  17. checkpoint-1200/optimizer.bin +3 -0
  18. checkpoint-1200/pytorch_lora_weights.safetensors +3 -0
  19. checkpoint-1200/random_states_0.pkl +3 -0
  20. checkpoint-1200/scaler.pt +3 -0
  21. checkpoint-1200/scheduler.bin +3 -0
  22. checkpoint-1300/optimizer.bin +3 -0
  23. checkpoint-1300/pytorch_lora_weights.safetensors +3 -0
  24. checkpoint-1300/random_states_0.pkl +3 -0
  25. checkpoint-1300/scaler.pt +3 -0
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  27. checkpoint-1400/optimizer.bin +3 -0
  28. checkpoint-1400/pytorch_lora_weights.safetensors +3 -0
  29. checkpoint-1400/random_states_0.pkl +3 -0
  30. checkpoint-1400/scaler.pt +3 -0
  31. checkpoint-1400/scheduler.bin +3 -0
  32. checkpoint-1500/optimizer.bin +3 -0
  33. checkpoint-1500/pytorch_lora_weights.safetensors +3 -0
  34. checkpoint-1500/random_states_0.pkl +3 -0
  35. checkpoint-1500/scaler.pt +3 -0
  36. checkpoint-1500/scheduler.bin +3 -0
  37. checkpoint-1600/optimizer.bin +3 -0
  38. checkpoint-1600/pytorch_lora_weights.safetensors +3 -0
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  40. checkpoint-1600/scaler.pt +3 -0
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  42. checkpoint-1700/optimizer.bin +3 -0
  43. checkpoint-1700/pytorch_lora_weights.safetensors +3 -0
  44. checkpoint-1700/random_states_0.pkl +3 -0
  45. checkpoint-1700/scaler.pt +3 -0
  46. checkpoint-1700/scheduler.bin +3 -0
  47. checkpoint-1800/optimizer.bin +3 -0
  48. checkpoint-1800/pytorch_lora_weights.safetensors +3 -0
  49. checkpoint-1800/random_states_0.pkl +3 -0
  50. checkpoint-1800/scaler.pt +3 -0
README.md ADDED
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+ ---
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+ tags:
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+ - stable-diffusion
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+ - stable-diffusion-diffusers
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+ - diffusers-training
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+ - text-to-image
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+ - diffusers
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+ - lora
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+ - template:sd-lora
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+ widget:
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+
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+ - text: 'in the style of TOK'
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+
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+ base_model: runwayml/stable-diffusion-v1-5
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+ instance_prompt: in the style of TOK
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+ license: openrail++
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+ ---
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+
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+ # SD1.5 LoRA DreamBooth - rayaanoidpr/wongkarwai_LoRa
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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 rayaanoidpr/wongkarwai_LoRa LoRA adaption weights for runwayml/stable-diffusion-v1-5.
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+
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+ ## Download model
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+
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+ ### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
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+
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+ - **LoRA**: download **[`wongkarwai_LoRa.safetensors` here 💾](/rayaanoidpr/wongkarwai_LoRa/blob/main/wongkarwai_LoRa.safetensors)**.
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+ - Place it on your `models/Lora` folder.
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+ - On AUTOMATIC1111, load the LoRA by adding `<lora:wongkarwai_LoRa:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
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+
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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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+
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+ pipeline = AutoPipelineForText2Image.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
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+ pipeline.load_lora_weights('rayaanoidpr/wongkarwai_LoRa', weight_name='pytorch_lora_weights.safetensors')
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+
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+ image = pipeline('in the style of TOK').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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+ ## Trigger words
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+
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+ You should use in the style of TOK to trigger the image generation.
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+
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+ ## Details
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+ All [Files & versions](/rayaanoidpr/wongkarwai_LoRa/tree/main).
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+
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+ The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sd15_advanced.py).
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+
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+ LoRA for the text encoder was enabled. False.
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+
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+ Pivotal tuning 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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