Instructions to use msilva/mapas_generados_ddpm2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use msilva/mapas_generados_ddpm2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("msilva/mapas_generados_ddpm2", 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

- Xet hash:
- d920c6fa79be47ea5e718a0831c446d59b5739b8460691c1164ed69d7b65fce7
- Size of remote file:
- 1.37 MB
- SHA256:
- 20e07f04d9e865225c82e551b48d15ff35c5b19c77c696d0f7b215a0ba6b5955
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