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---
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- text-to-image
- diffusers
- lora
- template:sd-lora
widget:
- text: a painting of a man sitting on a chair with a glass in the style of <s0><s1>
output:
url: image-0.png
- text: an indian painting depicting a woman and man in the style of <s0><s1>
output:
url: image-1.png
- text: an indian painting of a woman sitting and petting a peacock in the style of
<s0><s1>
output:
url: image-2.png
- text: an indian woman is taking a selfie with her husband in the style of <s0><s1>
output:
url: image-3.png
- text: a painting of a woman swinging on a swing in the style of <s0><s1>
output:
url: image-4.png
- text: an indian painting of a man holding a fish in the style of <s0><s1>
output:
url: image-5.png
- text: an indian painting depicting a bird and a man in the style of <s0><s1>
output:
url: image-6.png
- text: an indian painting depicting four women dancing in the style of <s0><s1>
output:
url: image-7.png
- text: an indian painting depicting a woman pouring water into a pot in the style
of <s0><s1>
output:
url: image-8.png
- text: a painting depicting two women carrying bricks in the style of <s0><s1>
output:
url: image-9.png
- text: an indian painting of a couple sitting on a couch in the style of <s0><s1>
output:
url: image-10.png
- text: an indian painting depicting a hindu goddess Kali in the style of <s0><s1>
output:
url: image-11.png
- text: a painting of two men in traditional clothing in the style of <s0><s1>
output:
url: image-12.png
- text: a painting of a woman playing a sitar in the style of <s0><s1>
output:
url: image-13.png
- text: a painting of a woman in a sari in the style of <s0><s1>
output:
url: image-14.png
- text: an indian painting of a man sitting on a chair in the style of <s0><s1>
output:
url: image-15.png
- text: an indian painting depicting a man sitting on a chariot in the style of <s0><s1>
output:
url: image-16.png
- text: an indian painting of a man sitting on a chair in the style of <s0><s1>
output:
url: image-17.png
- text: an indian painting depicting lord Shiva holding baby lord Ganesha in the style
of <s0><s1>
output:
url: image-18.png
- text: an old painting of a man sitting on a chair and a woman operating a handheld
fan in the style of <s0><s1>
output:
url: image-19.png
- text: an indian painting depicting lord Ganesha sitting on a tree in the style of
<s0><s1>
output:
url: image-20.png
- text: a painting of a woman sitting on a chair with a baby lord Ganesh in the style
of <s0><s1>
output:
url: image-21.png
- text: a painting of a woman carrying branches of a tree in the style of <s0><s1>
output:
url: image-22.png
- text: an indian painting of a man and woman in traditional clothing where man is
smoking a hookah in the style of <s0><s1>
output:
url: image-23.png
- text: an indian painting depicting a woman getting her hair done in the style of
<s0><s1>
output:
url: image-24.png
- text: a painting of a man sitting on a chair with a book in the style of <s0><s1>
output:
url: image-25.png
- text: an indian painting depicting two women in traditional clothing in the style
of <s0><s1>
output:
url: image-26.png
- text: a painting of a man playing a sitar in the style of <s0><s1>
output:
url: image-27.png
- text: an indian painting of a man smoking a pipe in the style of <s0><s1>
output:
url: image-28.png
- text: two women sitting on a yellow background with a brush in the style of <s0><s1>
output:
url: image-29.png
- text: an indian painting depicting a woman sitting on a couch brushing her hair
in the style of <s0><s1>
output:
url: image-30.png
- text: an indian painting depicting a woman and man quarrelling in the style of <s0><s1>
output:
url: image-31.png
- text: a painting of one men sitting on a chair and the other one on the floor in
the style of <s0><s1>
output:
url: image-32.png
- text: an indian painting of lord Ganesha sitting on a chair in the style of <s0><s1>
output:
url: image-33.png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: in the style of <s0><s1>
license: openrail++
---
# SDXL LoRA DreamBooth - rexoscare/kalighat-paintings-lora
<Gallery />
## Model description
### These are rexoscare/kalighat-paintings-lora 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 **[`kalighat-paintings-lora.safetensors` here 💾](/rexoscare/kalighat-paintings-lora/blob/main/kalighat-paintings-lora.safetensors)**.
- Place it on your `models/Lora` folder.
- On AUTOMATIC1111, load the LoRA by adding `<lora:kalighat-paintings-lora:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
- *Embeddings*: download **[`kalighat-paintings-lora_emb.safetensors` here 💾](/rexoscare/kalighat-paintings-lora/blob/main/kalighat-paintings-lora_emb.safetensors)**.
- Place it on it on your `embeddings` folder
- Use it by adding `kalighat-paintings-lora_emb` to your prompt. For example, `in the style of kalighat-paintings-lora_emb`
(you need both the LoRA and the embeddings as they were trained together for this LoRA)
## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
```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('rexoscare/kalighat-paintings-lora', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='rexoscare/kalighat-paintings-lora', filename='kalighat-paintings-lora_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](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
## 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](/rexoscare/kalighat-paintings-lora/tree/main).
The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py).
LoRA for the text encoder was enabled. False.
Pivotal tuning was enabled: True.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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