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modified: src/flux/util.py

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  1. src/flux/__pycache__/__init__.cpython-310.pyc +0 -0
  2. src/flux/__pycache__/_version.cpython-310.pyc +0 -0
  3. src/flux/__pycache__/math.cpython-310.pyc +0 -0
  4. src/flux/__pycache__/model.cpython-310.pyc +0 -0
  5. src/flux/__pycache__/sampling.cpython-310.pyc +0 -0
  6. src/flux/__pycache__/util.cpython-310.pyc +0 -0
  7. src/flux/modules/__pycache__/autoencoder.cpython-310.pyc +0 -0
  8. src/flux/modules/__pycache__/conditioner.cpython-310.pyc +0 -0
  9. src/flux/modules/__pycache__/layers.cpython-310.pyc +0 -0
  10. src/flux/util.py +1 -1
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src/flux/util.py CHANGED
@@ -137,7 +137,7 @@ def load_t5(device: str | torch.device = "cuda", max_length: int = 512) -> HFEmb
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  def load_clip(device: str | torch.device = "cuda") -> HFEmbedder:
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  #return HFEmbedder("openai/clip-vit-base-patch32", max_length=77, is_clip=True, torch_dtype=torch.bfloat16).to(device)
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- return HFEmbedder("models/text_encoder", max_length=77, is_clip=True, torch_dtype=torch.bfloat16).to(device)
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  def load_ae(name: str, device: str | torch.device = "cuda", hf_download: bool = True) -> AutoEncoder:
 
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  def load_clip(device: str | torch.device = "cuda") -> HFEmbedder:
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  #return HFEmbedder("openai/clip-vit-base-patch32", max_length=77, is_clip=True, torch_dtype=torch.bfloat16).to(device)
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+ return HFEmbedder("/home/user/app/models/text_encoder", max_length=77, is_clip=True, torch_dtype=torch.bfloat16).to(device)
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  def load_ae(name: str, device: str | torch.device = "cuda", hf_download: bool = True) -> AutoEncoder: