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: 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
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
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