import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Autodraft/CM2000112", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
creco-inference
Unified inference code for SageMaker and Hugging Face endpoints
Deployment
- Inference code (this) should be placed in the model folder respectively,
SageMaker
model/
code/
(repo) <-- The repo inference code as direct child (no sub-folder)
vae
unet
...
- Refer
deployment.ipynbfor creating endpoint.
Hugging Face
model/
(repo) <-- The repo inference code as direct child (no sub-folder)
vae
unet
...
- Refer doc to create endpoint.
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