Instructions to use Luffuly/unique3d-mvimage-diffuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Luffuly/unique3d-mvimage-diffuser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Luffuly/unique3d-mvimage-diffuser", 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
fix params save bug
Browse files- unet/mv_unet.py +2 -2
unet/mv_unet.py
CHANGED
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@@ -150,9 +150,9 @@ class UnifieldWrappedUNet(UNet2DConditionModel):
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):
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super().__init__(**{
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k: v for k, v in locals().items() if k not in
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["self", "kwargs", "__class__"]
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})
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-
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add_multiview_processor(
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model = self,
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enable_filter = lambda name: name.endswith(f"{multiview_attn_position}.processor"),
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):
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super().__init__(**{
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k: v for k, v in locals().items() if k not in
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+
["self", "kwargs", "__class__", "n_views", "num_modalities", "latent_size", "multiview_chain_pose"]
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})
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+
self.n_views = n_views
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add_multiview_processor(
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model = self,
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enable_filter = lambda name: name.endswith(f"{multiview_attn_position}.processor"),
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