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yangchen123321/lora-trained-sd3-dx_dg
lora-trained-sd3-dx_dg is a text-to-image model from yangchen123321. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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.safetensors14.2 MB · 73%
From the Hugging Face model README
These are yangchen123321/lora-trained-sd3-dx_dg DreamBooth LoRA weights for stabilityai/stable-diffusion-3-medium-diffusers.
The weights were trained using DreamBooth with the SD3 diffusers trainer.
Was LoRA for the text encoder enabled? False.
You should use Close-up of a high-voltage transmission line with steel-reinforced aluminum conductor over mountainous or forested terrain. The conductor shows a broken-strand defect: multiple aluminum strands fractured, loosened, and protruding, appearing frayed with exposed metallic ends, contrasting with intact twisted strands. Realistic industrial inspection photo, high resolution, sharp focus. to trigger the image generation.
Download the *.safetensors LoRA in the Files & versions tab.
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained(stabilityai/stable-diffusion-3-medium-diffusers, torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('yangchen123321/lora-trained-sd3-dx_dg', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('Close-up of a high-voltage transmission line with steel-reinforced aluminum conductor over mountainous or forested terrain. The conductor shows a broken-strand defect: multiple aluminum strands fractured, loosened, and protruding, appearing frayed with exposed metallic ends, contrasting with intact twisted strands. Realistic industrial inspection photo, high resolution, sharp focus.').images[0]
diffusers_lora_weights.safetensors here 💾.
models/Lora folder.<lora:your_new_name:1> to your prompt. On ComfyUI just load it as a regular LoRA.For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
Please adhere to the licensing terms as described here.
# TODO: add an example code snippet for running this diffusion pipeline
[TODO: provide examples of latent issues and potential remediations]
[TODO: describe the data used to train the model]