SDXL LoRA DreamBooth - computational-mama/corporateshwari

Prompt
<s0><s1> a beautiful painting of a tired young mother like an indian goddess, flying away to heaven with children on her shoulder, laptop in her lap, in the style of Raja Ravi Varma

Prompt
<s0><s1> a beautiful painting of a young indian mother with many arms like an indian goddess sitting on a rock with a child on her arms, and a laptop in her arms, there are cherubs in the background, in the style of Raja Ravi Varma

Prompt
<s0><s1> a beautiful painting of a young indian mother with many arms like an indian goddess sitting on a cloud with a child on her arms, and a laptop in her arms, in the style of Raja Ravi Varma

Prompt
<s0><s1> a beautiful painting of a young indian mother with an indian goddess flying in the air with a child on her arms, there are cherubs in the background, in the style of Raja Ravi Varma

Prompt
<s0><s1> a beautiful painting of a young indian mother with an indian goddess flying in the air with a child on her arms, in the style of Raja Ravi Varma

Prompt
<s0><s1> a beautiful painting of a tired young mother in a corporate suit like an indian goddess, flying away to heaven, laptop in her lap, there are cherubs in the background, in the style of Raja Ravi Varma

Model description

These are computational-mama/corporateshwari 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 corporateshwari.safetensors here 💾.
- Place it on your models/Lora folder.
- On AUTOMATIC1111, load the LoRA by adding <lora:corporateshwari:1> to your prompt. On ComfyUI just load it as a regular LoRA.
Embeddings: download corporateshwari_emb.safetensors here 💾.
- Place it on it on your embeddings folder
- Use it by adding corporateshwari_emb to your prompt. (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('computational-mama/corporateshwari', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='computational-mama/corporateshwari', filename='corporateshwari_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('<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.

computational-mama-research
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corporateshwari