Instructions to use SargeZT/velocipedeux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SargeZT/velocipedeux with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SargeZT/velocipedeux", 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
- Draw Things
- DiffusionBee
Model Card for Velocipedeux
A Stable Diffusion 1.5 model finetuned with v-prediction, zero terminal SNR, and trailing timesteps using a diverse dataset.
Model Details
Model Description
This model is a finetune of Stable Diffusion 1.5 that implements Zero Terminal SNR scaling, V-Prediction, and the use of trailing timesteps during training.
This model is in active development and should not be considered final.
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