Fix loading problem
Browse files
app.py
CHANGED
@@ -9,6 +9,7 @@ from pikigen import PikigenPipeline
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# Trick required because it is not a native diffusers model
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from diffusers.pipelines.pipeline_loading_utils import LOADABLE_CLASSES, ALL_IMPORTABLE_CLASSES
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LOADABLE_CLASSES.setdefault("pikigen", {}).setdefault("DiT", []).extend(["save_pretrained", "from_pretrained"])
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ALL_IMPORTABLE_CLASSES.setdefault("DiT", []).extend(["save_pretrained", "from_pretrained"])
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device = "cuda" if torch.cuda.is_available() else "cpu"
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@@ -20,7 +21,7 @@ else:
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torch_dtype = torch.float32
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pipe = PikigenPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
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pipe.enable_model_cpu_offload() # For less memory consumption
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pipe.vae.enable_slicing()
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pipe.vae.enable_tiling()
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# Trick required because it is not a native diffusers model
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from diffusers.pipelines.pipeline_loading_utils import LOADABLE_CLASSES, ALL_IMPORTABLE_CLASSES
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LOADABLE_CLASSES.setdefault("pikigen", {}).setdefault("DiT", []).extend(["save_pretrained", "from_pretrained"])
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LOADABLE_CLASSES["pikigen.model"] = LOADABLE_CLASSES["pikigen"]
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ALL_IMPORTABLE_CLASSES.setdefault("DiT", []).extend(["save_pretrained", "from_pretrained"])
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device = "cuda" if torch.cuda.is_available() else "cpu"
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torch_dtype = torch.float32
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pipe = PikigenPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
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# pipe.enable_model_cpu_offload() # For less memory consumption
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pipe.vae.enable_slicing()
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pipe.vae.enable_tiling()
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