Instructions to use openskyml/overall-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use openskyml/overall-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("openskyml/overall-v1", 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
metadata
inference:
parameters:
steps: 50
guidance_scale: 7
width: 512
height: 512
license: other
license_name: overall-license
license_link: https://hf.co/openskyml/overall-v1/blob/main/OVERALL-LICENSE.txt
tags:
- text-to-image
- diffusion
- overall
- openskyml
library_name: diffusers
pipeline_tag: text-to-image
Overall V1
Overall is not just an ordinary Diffusion model, it was trained on a huge image dataset, and you can use it freely right now!
Model Details
Model Description
The model was trained using Dreambooth Training based on the Stable Diffusion 1.5 model.
- Developed by: OpenSkyML
- Model type: Text-to-Image
- License: Overall License