cxr_gen_models
Collection
7 items β’ Updated
How to use P-RAJIV/cxr_stable_diffusion_sdxl_lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("P-RAJIV/cxr_stable_diffusion_sdxl_lora")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("P-RAJIV/cxr_stable_diffusion_sdxl_lora")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]This repository provides LoRA weights for SDXL fine-tuned on chest X-ray data.
Base model required: stabilityai/stable-diffusion-xl-base-1.0.
import torch
from diffusers import StableDiffusionXLPipeline
pipe = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16
).to("cuda")
pipe.load_lora_weights("P-RAJIV/cxr_stable_diffusion_sdxl_lora")
prompt = "High resolution chest X-ray with lung opacity"
image = pipe(prompt, num_inference_steps=30, guidance_scale=7.5).images[0]
image.save("output.png")
π§ͺ Example Prompts
"Normal chest X-ray"
"Chest X-ray showing cardiomegaly"
"Lung opacity in right lower lobe"
"Severe pneumonia chest radiograph"
β οΈ Limitations
Generated images are synthetic and not for clinical use
May produce anatomically inconsistent outputs
Performance depends heavily on prompt quality
π Training Details
Base Model: Stable Diffusion v1.5
Domain: Chest X-ray imaging
Fine-tuning: Text-to-image diffusion training
π§ Intended Use
Research in medical imaging
Data augmentation
Diffusion model experimentation
β Disclaimer
This model is not intended for medical diagnosis or clinical decision-making.