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rupa

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lora
replicate
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metadata
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

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 

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