Instructions to use kiigii/imagedream-ipmv-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kiigii/imagedream-ipmv-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kiigii/imagedream-ipmv-diffusers", 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
Update pipeline_imagedream.py
Browse files- pipeline_imagedream.py +1 -1
pipeline_imagedream.py
CHANGED
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@@ -193,7 +193,7 @@ class ImageDreamPipeline(StableDiffusionPipeline):
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if cross_attention_kwargs is None:
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num_views = self.num_views
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else:
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cross_attention_kwargs.pop("num_views", self.num_views)
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# 0. Default height and width to unet
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height = height or self.unet.config.sample_size * self.vae_scale_factor
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if cross_attention_kwargs is None:
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num_views = self.num_views
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else:
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+
num_views = cross_attention_kwargs.pop("num_views", self.num_views)
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# 0. Default height and width to unet
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height = height or self.unet.config.sample_size * self.vae_scale_factor
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