Leo Cat Sdxl Lora V2

🚀 SDXL LoRA DreamBooth - greerben0/leo-cat-sdxl-lora-v2

This project provides LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0, enabling the generation of images featuring a LEO cat.

🚀 Quick Start

✨ Features

• These are greerben0/leo-cat-sdxl-lora-v2 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
• It can be used with various UIs and the 🧨 diffusers library.

📦 Installation

Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke

• LoRA: download leo-cat-sdxl-lora-v2.safetensors here 💾.
  • Place it on your models/Lora folder.
  • On AUTOMATIC1111, load the LoRA by adding <lora:leo-cat-sdxl-lora-v2:1> to your prompt. On ComfyUI just load it as a regular LoRA.
• Embeddings: download leo-cat-sdxl-lora-v2_emb.safetensors here 💾.
  • Place it on it on your embeddings folder
  • Use it by adding leo-cat-sdxl-lora-v2_emb to your prompt. For example, photo of a LEO cat (you need both the LoRA and the embeddings as they were trained together for this LoRA)

💻 Usage Examples

Basic Usage

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('greerben0/leo-cat-sdxl-lora-v2', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='greerben0/leo-cat-sdxl-lora-v2', filename='leo-cat-sdxl-lora-v2_emb.safetensors', repo_type="model")
state_dict = load_file(embedding_path)
pipeline.load_textual_inversion(state_dict["clip_l"], token=[], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
pipeline.load_textual_inversion(state_dict["clip_g"], token=[], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
        
image = pipeline('a LEO cat on the floor').images[0]

📚 Documentation

• 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

🔧 Technical 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.

📄 License

The license for this project is openrail++.