Create README.md

README.md

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+---
+license: openrail++
+library_name: diffusers
+tags:
+- text-to-image
+- text-to-image
+- diffusers-training
+- diffusers
+- lora
+- template:sd-lora
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+base_model: SG161222/RealVisXL_V4.0
+instance_prompt: a headshot of a sks person
+widget:
+- text: closeup portrait photo of a sks person in dark clothes, city street, neon, fog, volumetric
+    wearing business outfit, grey background
+  output:
+    url: image_0.png
+- text: closeup portrait photo of a sks person in dark clothes, city street, neon, fog, volumetric
+    wearing business outfit, grey background
+  output:
+    url: image_1.png
+- text: closeup portrait photo of a sks person in dark clothes, city street, neon, fog, volumetric
+    wearing business outfit, grey background
+  output:
+    url: image_2.png
+- text: closeup portrait photo of a sks person in dark clothes, city street, neon, fog, volumetric
+    wearing business outfit, grey background
+  output:
+    url: image_3.png
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+# SDXL LoRA DreamBooth - yehiaa/lora-trained-xl-drew
+
+<Gallery />
+
+## Model description
+
+These are yehiaa/lora-trained-xl-drew LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
+
+The weights were trained  using [DreamBooth](https://dreambooth.github.io/).
+
+LoRA for the text encoder was enabled: False.
+
+Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
+
+## Trigger words
+
+You should use a headshot of a sks person to trigger the image generation.
+
+## Download model
+
+Weights for this model are available in Safetensors format.
+
+[Download](yehiaa/lora-trained-xl-drew/tree/main) them in the Files & versions tab.
+
+
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+# TODO: add an example code snippet for running this diffusion pipeline
+```
+
+#### Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training details
+
+[TODO: describe the data used to train the model]