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modified: src/flux/modules/conditioner.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/modules/conditioner.py +1 -1
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src/flux/modules/conditioner.py CHANGED
@@ -12,7 +12,7 @@ class HFEmbedder(nn.Module):
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  if self.is_clip:
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  #self.tokenizer: CLIPTokenizer = CLIPTokenizer.from_pretrained(version, max_length=max_length)
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- self.tokenizer: CLIPTokenizer = CLIPTokenizer.from_pretrained("/home/user/app/models/tokenizer", max_length=max_length)
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  self.hf_module: CLIPTextModel = CLIPTextModel.from_pretrained(version, **hf_kwargs)
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  else:
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  self.tokenizer: T5Tokenizer = T5Tokenizer.from_pretrained(version, max_length=max_length)
 
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  if self.is_clip:
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  #self.tokenizer: CLIPTokenizer = CLIPTokenizer.from_pretrained(version, max_length=max_length)
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+ self.tokenizer: CLIPTokenizer = CLIPTokenizer.from_pretrained("/home/user/app/models/tokenizer", max_length=max_length, truncation=True)
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  self.hf_module: CLIPTextModel = CLIPTextModel.from_pretrained(version, **hf_kwargs)
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  else:
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  self.tokenizer: T5Tokenizer = T5Tokenizer.from_pretrained(version, max_length=max_length)