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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: RG2027
widget:
- text: >-
The man in the image stands in a natural setting with a beautiful
mountainous backdrop under a clear blue sky with a few light clouds. He is
wearing a long-sleeved athletic jacket in white, featuring a mountain map
design with soft brown lines on the sleeves and body, along with a prominent
light brown pocket on the chest and a smaller pocket on the left side of the
waist. The jacket has a high collar in the same brown color. The fabric
looks comfortable and light, likely made from cotton or nylon, suitable for
outdoor activities. He wears black shorts that match the sporty design, made
of a lightweight and practical fabric like nylon or light cotton, allowing
him to move freely while walking in nature. His shoes are white athletic
sneakers with a sturdy design, ideal for outdoor activities like hiking or
walking, paired with long white socks featuring simple brown patterns that
complement the jacket. The lighting is entirely natural, with the sun low in
the sky, casting a soft golden hue that reflects off his clothing and skin,
enhancing the natural ambiance. The background consists of distant mountains
covered in greenery and a ground filled with dry grass that matches the warm
atmosphere, evoking a sense of outdoor adventure.
output:
url: images/example_u53p1lone.png
---
# Rg2027
<!-- <Gallery /> -->
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
## Trigger words
You should use `RG2027` 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('renoomon/RG2027', 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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