metadata

base_model: CompVis/stable-diffusion-v1-4
library_name: diffusers
license: creativeml-openrail-m
inference: true
tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - diffusers
  - diffusers-training
  - lora

LoRA text2image fine-tuning - RiddleHe/SD14_pathology_lora

These are LoRA adaption weights for CompVis/stable-diffusion-v1-4. The weights were fine-tuned on the None dataset. You can find some example images in the following.

Intended uses & limitations

How to use

pipe = DiffusionPipeline.from_pretrained(
  "CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16
)

pipe.load_lora_weights("RiddleHe/SD14_pathology_lora")
pipe.to('cuda')

prompt = "A histopathology image of breast cancer tissue"

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

This model is trained on 28216 breast cancer tissue images from the BRCA dataset.