Text-to-Image
Diffusers
Safetensors
StableDiffusionXLPipeline
stable-diffusion-xl
stable-diffusion-xl-diffusers
diffusers-training
Instructions to use sergshymko/trained_sdxl5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sergshymko/trained_sdxl5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sergshymko/trained_sdxl5", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Text-to-image finetuning - sergshymko/trained_sdxl5
This pipeline was finetuned from stabilityai/stable-diffusion-xl-base-1.0 on the sergshymko/testdataset14 dataset. Below are some example images generated with the finetuned pipeline using the following prompt: A young male playing basketball on the school stadium in the morning.:
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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 sergshymko/trained_sdxl5
Base model
stabilityai/stable-diffusion-xl-base-1.0


