Helios-OrthoJoint

Helios OrthoJoint

Model Description

Helios-OrthoJoint is a Stable Diffusion 1.5 LoRA fine-tuned for generating high-quality orthopedic and medical joint imagery. Designed for healthcare AI applications including medical illustration, patient education, and synthetic data generation for joint anatomy.

Model Architecture

• Base Model: Stable Diffusion v1.5 (runwayml/stable-diffusion-v1-5)
• Fine-tuning Method: LoRA (Low-Rank Adaptation)
• Framework: Diffusers / Kohya-SS
• Task: Text-to-Image Generation (Medical Domain)

Training Details

• Training Tool: Kohya-SS LoRA trainer
• Domain: Orthopedic / Joint medical imagery
• Trigger Words: Use medical/orthopedic descriptors in prompts for best results
• Steps: Fine-tuned to convergence on curated orthopedic image dataset

Files

Usage

from diffusers import StableDiffusionPipeline
import torch
from huggingface_hub import hf_hub_download

# Download LoRA weights
lora_path = hf_hub_download(repo_id='devanshty/Helios-OrthoJoint', filename='Helios_OrthoJoint_v1.safetensors')

# Load base pipeline
pipe = StableDiffusionPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5",
    torch_dtype=torch.float16
).to("cuda")

# Load LoRA weights
pipe.load_lora_weights(lora_path)

# Generate
image = pipe("orthopedic knee joint X-ray, medical illustration, high detail").images[0]
image.save("output.png")

Download & Use

from huggingface_hub import hf_hub_download
lora_path = hf_hub_download(repo_id='devanshty/Helios-OrthoJoint', filename='Helios_OrthoJoint_v1.safetensors')

Disclaimer

Generated images are for research and educational use only and should not be used for clinical diagnosis.