End of training

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+image_0.png filter=lfs diff=lfs merge=lfs -text
+image_1.png filter=lfs diff=lfs merge=lfs -text
+image_2.png filter=lfs diff=lfs merge=lfs -text
+image_3.png filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+tags:
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+- text-to-image
+- diffusers
+- lora
+- template:sd-lora
+widget:
+
+        - text: 'a TOK woman with pink hair at a party'
+          output:
+            url:
+                "image_0.png"
+        
+        - text: 'a TOK woman with pink hair at a party'
+          output:
+            url:
+                "image_1.png"
+        
+        - text: 'a TOK woman with pink hair at a party'
+          output:
+            url:
+                "image_2.png"
+        
+        - text: 'a TOK woman with pink hair at a party'
+          output:
+            url:
+                "image_3.png"
+        
+base_model: stabilityai/stable-diffusion-xl-base-1.0
+instance_prompt: photo of a TOK woman
+license: openrail++
+---
+
+# SDXL LoRA DreamBooth - linoyts/linoy_lora_unet
+
+<Gallery />
+
+## Model description
+
+### These are linoyts/linoy_lora_unet LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
+
+## Download model
+
+### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
+
+- **LoRA**: download **[`linoy_lora_unet.safetensors` here 💾](/linoyts/linoy_lora_unet/blob/main/linoy_lora_unet.safetensors)**.
+    - Place it on your `models/Lora` folder.
+    - On AUTOMATIC1111, load the LoRA by adding `<lora:linoy_lora_unet:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
+
+
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
+
+```py
+from diffusers import AutoPipelineForText2Image
+import torch
+
+pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
+pipeline.load_lora_weights('linoyts/linoy_lora_unet', weight_name='pytorch_lora_weights.safetensors')
+
+image = pipeline('a TOK woman with pink hair at a party').images[0]
+```
+
+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)
+
+## Trigger words
+
+You should use photo of a TOK woman to trigger the image generation.
+
+## Details
+All [Files & versions](/linoyts/linoy_lora_unet/tree/main).
+
+The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py).
+
+LoRA for the text encoder was enabled. False.
+
+Pivotal tuning was enabled: False.
+
+Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
+

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