metadata

datasets:
  - cookey39/blue_reflection
language:
  - en

SDXL LoRA DreamBooth - cookey39/reflector

Examples:

https://www.pixiv.net/artworks/119270564

https://www.pixiv.net/artworks/119269797

Model description

These are cookey39/reflector LoRA adaption weights for cookey39/hyper-sd-8step.

Download model

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

LoRA: download reflector.safetensors here 💾.
- Place it on your models/Lora folder.
- On AUTOMATIC1111, load the LoRA by adding <lora:reflector:1> to your prompt. On ComfyUI just load it as a regular LoRA.
Embeddings: download reflector_emb.safetensors here 💾.
- Place it on it on your embeddings folder
- Use it by adding reflector_emb to your prompt. For example, blue_reflection: (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
from diffusers import DiffusionPipeline, DDIMScheduler
import torch
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file
        
pipeline = AutoPipelineForText2Image.from_pretrained('cookey39/reflector', torch_dtype=torch.float16).to('cuda')

# lower eta results in more detail
instance_token = "<s0><s1>"
prompt = f"a {instance_token}masterpiece, best quality,long hair, cute face, white kneehighs, black hair, hair strand, twin braids, cat hair ornament, adorable girl, absurdres, huge_filesize, Japanese, game_cg, {instance_token}  "
negative_prompt = "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, bad feet, "
image = pipeline(prompt=prompt, negative_prompt = negative_prompt, num_inference_steps=50, cross_attention_kwargs={"scale": 1.0},width = 720, height=1080).images[0]
image

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: None.