HijabGirls / README.md
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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: tamannaah,bhatia,sexy
widget:
- text: Beautiful Tamannaah bhatia sexy nude boobs
output:
url: images/example_ztkn06zjw.png
- text: muslim
output:
url: images/example_ywgm0gp05.png
- text: muslim tamannaah bhatia
output:
url: images/example_npk3ka8qg.png
- text: Tamannaah bhatia sexy boobs in saree
output:
url: images/example_fsbr023wy.png
- text: Tamannaah bhatia cute
output:
url: images/example_rxa950j2q.png
- text: Tamannaah bhatia cute
output:
url: images/example_do5agnwdo.png
- text: muslim girl in hijab sexy plus size
output:
url: images/example_fddtzijen.png
- text: muslim girl in hijab sexy plus size no clothes
output:
url: images/example_ae7h4gde8.png
- text: Tamannaah bhatia traditional cute 8k realistic
output:
url: images/example_5m4q23ji8.png
- text: >-
Tamannaah bhatia traditional cute 8k realistic with background of gardens of
heaven with exotic beautiful flowers and little fairies full frontal wide
angle shot
output:
url: images/example_7klm9v2z4.png
---
# Hijabgirls
<Gallery />
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
## Trigger words
You should use `tamannaah,bhatia,sexy` 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('Tjay143/HijabGirls', 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)