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output_multi_sd1

Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
diffusers-training
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output_multi_sd1 / README.md
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metadata
base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
library_name: diffusers
license: creativeml-openrail-m
inference: true
tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - diffusers
  - controlnet
  - diffusers-training

controlnet-maxpmx/output_multi_sd1

These are controlnet weights trained on stable-diffusion-v1-5/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.

prompt: denoised image images_0) prompt: denoised image images_1) prompt: super-resolution ER image images_2) prompt: super-resolution F-actin image images_3) prompt: super-resolution Microtubules image images_4) prompt: Generate the corresponding DAPI protein image images_5) prompt: Generate the corresponding CD11B protein image images_6) prompt: Generate the corresponding DAPI protein image images_7) prompt: Generate the corresponding CD11B protein image images_8) prompt: Generate the corresponding DAPI protein image images_9) prompt: Generate the corresponding CD11B protein image images_10) prompt: CD68 RNA expression images_11) prompt: CXCR4 RNA expression images_12)

Intended uses & limitations

How to use 

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

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

Training details

[TODO: describe the data used to train the model]