huggy_lora_edm_v1 / README.md
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metadata
tags:
  - stable-diffusion-xl
  - stable-diffusion-xl-diffusers
  - diffusers-training
  - text-to-image
  - diffusers
  - lora
  - template:sd-lora
  - edm-training
inference:
  parameters:
    scheduler: EulerDiscreteScheduler
widget:
  - text: a TOK emoji dressed as an easter bunny
    output:
      url: image_0.png
  - text: a TOK emoji dressed as an easter bunny
    output:
      url: image_1.png
  - text: a TOK emoji dressed as an easter bunny
    output:
      url: image_2.png
  - text: a TOK emoji dressed as an easter bunny
    output:
      url: image_3.png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: a TOK emoji
license: openrail++

SDXL LoRA DreamBooth - linoyts/huggy_lora_edm_v1

Prompt
a TOK emoji dressed as an easter bunny
Prompt
a TOK emoji dressed as an easter bunny
Prompt
a TOK emoji dressed as an easter bunny
Prompt
a TOK emoji dressed as an easter bunny

Model description

These are linoyts/huggy_lora_edm_v1 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

Use it with the 🧨 diffusers library

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/huggy_lora_edm_v1', weight_name='pytorch_lora_weights.safetensors')

image = pipeline('a TOK emoji dressed as an easter bunny').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

Trigger words

You should use a TOK emoji to trigger the image generation.

Details

All Files & versions.

The weights were trained using 🧨 diffusers Advanced Dreambooth Training Script.

LoRA for the text encoder was enabled. False.

Pivotal tuning was enabled: False.

Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.