Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion-xl
stable-diffusion-xl-diffusers
controlnet
diffusers-training
Instructions to use shreyasvivek-kulkarni/OUTPUT_DIR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shreyasvivek-kulkarni/OUTPUT_DIR with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("shreyasvivek-kulkarni/OUTPUT_DIR") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline
controlnet = ControlNetModel.from_pretrained("shreyasvivek-kulkarni/OUTPUT_DIR")
pipe = StableDiffusionControlNetPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet
)controlnet-shreyasvivek-kulkarni/OUTPUT_DIR
These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning. You can find some example images below.
prompt: a close up of a man with a mohawkcut and a purple shirt
prompt: a close up of a man in a suit and tie with a green tie

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]
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Model tree for shreyasvivek-kulkarni/OUTPUT_DIR
Base model
stabilityai/stable-diffusion-xl-base-1.0