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---
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
language:
- en
tags:
- flux
- diffusers
- lora
- replicate
base_model: black-forest-labs/FLUX.1-dev
pipeline_tag: text-to-image
instance_prompt: rup
widget:
- text: >-
straight view face close-up of A beautiful naked white woman seeing camera
is inside the waterfall, (((completely surrounded by the water))) as it
cascades down from above and all around her. She is in a hidden space behind
the waterfall, where the water forms a shimmering curtain in front of her,
(((completely obscuring her from view))). The water rushes down around her,
creating a sense of enclosure and seclusion within the waterfall itself. Her
long wet hair clings to her face and shoulders, and the mist from the
waterfall adds a mystical aura to the scene. The lush greenery outside is
visible through the veil of water, but she remains tucked away in this
intimate, secret space within the waterfall. her eyes are closed. her mouth
is open. her head is tilted up looking into the cascading curtain of water
as she gets drenched in falling water. her hair is soaking wet, her caramel
skin is soaking wet, water is dripping from her body and hair, water
droplets on her face, water dripping from her face, chin and nose, water
droplets create a wet water effect,<lora:Wet_Face_Effect:1.5>, (((extremely
straight deep side part thick black hairstyle)))
output:
url: images/example_qie4wiwj6.png
---
# Rupa
<!-- <Gallery /> -->
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
## Trigger words
You should use `rup` to trigger the image generation.
## 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.float16).to('cuda')
pipeline.load_lora_weights('harshasai-dev/rupa', weight_name='lora.safetensors')
image = pipeline('your prompt').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)
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