CoolFace
Modelpublic

dataautogpt3/synthetic-anime

sourceHugging Faceopenrail++updated 3y agoView on Hugging Face
2likes69downloads
Model Card

SDXL LoRA DreamBooth - dataautogpt3/synthetic-anime

<Gallery />

Model description

These are dataautogpt3/synthetic-anime 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

  • โ€”LoRA: download [`synthetic-anime.safetensors` here ๐Ÿ’พ](/dataautogpt3/synthetic-anime/blob/main/synthetic-anime.safetensors).
  • โ€”Place it on your models/Lora folder.
  • โ€”On AUTOMATIC1111, load the LoRA by adding <lora:synthetic-anime:1> to your prompt. On ComfyUI just load it as a regular LoRA.
  • โ€”Embeddings: download [`synthetic-anime_emb.safetensors` here ๐Ÿ’พ](/dataautogpt3/synthetic-anime/blob/main/synthetic-anime_emb.safetensors).
  • โ€”Place it on it on your embeddings folder
  • โ€”Use it by adding synthetic-anime_emb to your prompt. For example, in the style of synthetic-anime_emb (you need both the LoRA and the embeddings as they were trained together for this LoRA)

Use it with the ๐Ÿงจ diffusers library

py
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('dataautogpt3/synthetic-anime', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='dataautogpt3/synthetic-anime', filename='synthetic-anime_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('in the style 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 โ†’ use <s0><s1> in your prompt

Details

All Files & versions.

LoRA for the text encoder was enabled. False.

Pivotal tuning was enabled: True.

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