doctor-diffusion-s-xray-xl-lora-0

Doctor Diffusion's Xray XL LoRA

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Model description

<p><span style="color:rgb(193, 194, 197)">Use "</span><strong>xray</strong><span style="color:rgb(193, 194, 197)">" in the front of your prompt.</span><br /><br /><strong>Experimental: </strong><span style="color:rgb(193, 194, 197)">This is the first version of this LoRA and it may not always work as desired. If you get poor results please share in the comments so I can improve v2.</span><br /><br /><span style="color:rgb(17, 17, 17)">☕ </span><span style="color:rgb(193, 194, 197)">Like what I do? </span><span style="color:rgb(17, 17, 17)">☕</span><br /><span style="color:rgb(17, 17, 17)">☕ </span><a target="_blank" rel="ugc" href="https://www.buymeacoffee.com/doctordiffusion">Donations allow me to continue to make more as an independent researcher</a><span style="color:rgb(193, 194, 197)">! </span><span style="color:rgb(17, 17, 17)">☕</span><br /><br /><strong>The history of x-rays:</strong><br />X-ray scans were first developed by Wilhelm Conrad Röntgen in 1895 and are widely used in medical diagnostics. They work by passing electromagnetic radiation through the body, capturing an image of internal structures like bones and organs based on their density. Over time, advancements have led to methods such as CT scans and MRI for more detailed imaging without ionizing radiation.</p>

Trigger words

You should use xray to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('DoctorDiffusion/doctor-diffusion-s-xray-xl-lora', weight_name='DD-xray-v1.safetensors')
image = pipeline('`xray`').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers