Instructions to use Svatai/svatai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Svatai/svatai with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Svatai/svatai", 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
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Svatai/svatai", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Svat AI, an advanced text-to-image generation model with 16.8 billion parameters, specifically designed to create high-clarity and extremely detailed images from a wide range of text prompts. Whether your input is a single word or a complex sentence, Svat AI excels at producing visually striking results that push the boundaries of what’s possible in AI image generation. Led by a small, dedicated team, Svat AI is shaping the future of AI, striving to make advanced technology more accessible to everyone. With ambitious plans to expand into text-to-video, text-to-movie, text-to-show, and beyond, Svat AI is setting new benchmarks in the AI industry.
Learn more at www.svatai.com or contact us at info@svatai.com if you'd like to join our team or collaborate.
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