README.md

metadata

tags:
  - stable-diffusion-xl
  - stable-diffusion-xl-diffusers
  - text-to-image
  - diffusers
  - lora
  - template:sd-lora
widget:
  - text: A photo of <s0><s1> a man holding up a passport and an eagle
    output:
      url: image-0.png
  - text: A photo of <s0><s1> a man with a beard and a black shirt
    output:
      url: image-1.png
  - text: A photo of <s0><s1> a man taking a selfie in front of a colorful building
    output:
      url: image-2.png
  - text: A photo of <s0><s1> a man in a blue scrub suit and hat
    output:
      url: image-3.png
  - text: A photo of <s0><s1> a man holding up a piece of wood with a note on it
    output:
      url: image-4.png
  - text: A photo of <s0><s1> a man with a beard and a black shirt
    output:
      url: image-5.png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: A photo of <s0><s1>
license: openrail++

SDXL LoRA DreamBooth - saddad/criley

Prompt

A photo of <s0><s1> a man holding up a passport and an eagle

Prompt

A photo of <s0><s1> a man with a beard and a black shirt

Prompt

A photo of <s0><s1> a man taking a selfie in front of a colorful building

Prompt

A photo of <s0><s1> a man in a blue scrub suit and hat

Prompt

A photo of <s0><s1> a man holding up a piece of wood with a note on it

Prompt

A photo of <s0><s1> a man with a beard and a black shirt

Model description

These are saddad/criley 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 criley.safetensors here 💾.
  • Place it on your models/Lora folder.
  • On AUTOMATIC1111, load the LoRA by adding <lora:criley:1> to your prompt. On ComfyUI just load it as a regular LoRA.
• Embeddings: download criley_emb.safetensors here 💾.
  • Place it on it on your embeddings folder
  • Use it by adding criley_emb to your prompt. For example, A photo of criley_emb (you need both the LoRA and the embeddings as they were trained together for this LoRA)

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file
        
pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('saddad/criley', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='saddad/criley', filename='criley_emb.safetensors' repo_type="model")
state_dict = load_file(embedding_path)
pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
pipeline.load_textual_inversion(state_dict["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
        
image = pipeline('A photo of <s0><s1>').images[0]

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

Trigger words

To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens:

to trigger concept TOK → use <s0><s1> in your prompt

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: True.

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