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metadata
library_name: diffusers
tags:
  - text-to-image
from diffusers import DiffusionPipeline
pipeline = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-sdxl-custom-all", trust_remote_code=True)

assert pipeline.config.unet == ('diffusers_modules.local.my_unet_model', 'MyUNetModel')
assert pipeline.config.scheduler == ('diffusers_modules.local.my_scheduler', 'MyScheduler')
assert pipeline.__class__.__name__ == "MyPipeline"

pipeline = pipeline.to(torch_device)
images = pipeline("test", num_inference_steps=2, output_type="np")[0]

assert images.shape == (1, 64, 64, 3)