pasosart-style / README.md
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Add generated example (#3)
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---
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- ai-toolkit
widget:
- text: A person in a bustling cafe in the style of pasosart
output:
url: samples/1727682751598__000001000_0.jpg
- text: >-
woman with purple hair, wearing purple sunglasses, white and purple kimono
looking at the camera with confidence, pink background in the style of
pasosart
output:
url: images/example_iwtwv58sk.png
- text: >-
girl with white hair, wearing specs, white and bluish dress thinking about
something, applying lipstick, full portrait, light blue background, with
water elements around her
output:
url: images/example_j1efuavv5.png
- text: >-
a girl holding a sword, she has white hair with a headband and eye band, she
is wearing a black and white apparel with yellow design lines, white
background, short hair in the style of pasosart
output:
url: images/example_tsdnabxrv.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: in the style of pasosart
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
---
# pasosart-style
Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
<Gallery />
## Trigger words
You should use `in the style of pasosart` to trigger the image generation.
## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
[Download](/jayavibhav/pasosart-style/tree/main) them in the Files & versions tab.
## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
```py
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('jayavibhav/pasosart-style', weight_name='pasosart-style')
image = pipeline('A person in a bustling cafe in the style of pasosart').images[0]
image.save("my_image.png")
```
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)