Instructions to use lauluCas/turtles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lauluCas/turtles with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lauluCas/turtles", 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
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("lauluCas/turtles", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Model Card for turtles, part of module 2 DX481 data driven-arts
This model is a diffusion model for unconditional image generation of turtles Trained for 50 epochs -ne3w params
Usage
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('lauluCas/turtles').to(device)
image = pipeline().images[0]
image
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