commit files to HF hub
Browse files- .gitattributes +1 -0
- __pycache__/deepfakemodel.cpython-39.pyc +3 -0
- deepfakeconfig.py +1 -4
- deepfakemodel.py +5 -2
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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__pycache__/deepfakemodel.cpython-39.pyc filter=lfs diff=lfs merge=lfs -text
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__pycache__/deepfakemodel.cpython-39.pyc
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:5bbb956437a3f70cad4bb133c5063b93a9080c4f144a65a83648c7694982e185
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size 872
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deepfakeconfig.py
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@@ -4,7 +4,4 @@ class DeepFakeConfig(PretrainedConfig):
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model_type = "ResNet"
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def __init__(self,**kwargs):
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super().__init__(**kwargs)
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self.DEVICE = 'cuda:0' if torch.cuda.is_available() else 'cpu'
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config = DeepFakeConfig()
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config.register_for_auto_class()
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model_type = "ResNet"
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def __init__(self,**kwargs):
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super().__init__(**kwargs)
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self.DEVICE = 'cuda:0' if torch.cuda.is_available() else 'cpu'
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deepfakemodel.py
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from transformers import PreTrainedModel
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from facenet_pytorch import MTCNN, InceptionResnetV1
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from deepfakeconfig import DeepFakeConfig
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config = DeepFakeConfig()
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class DeepFakeModel(PreTrainedModel):
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config_class = DeepFakeConfig
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@@ -12,4 +11,8 @@ class DeepFakeModel(PreTrainedModel):
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classify=True,
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num_classes=1,
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device=config.DEVICE
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)
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from transformers import PreTrainedModel
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from facenet_pytorch import MTCNN, InceptionResnetV1
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from deepfakeconfig import DeepFakeConfig
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class DeepFakeModel(PreTrainedModel):
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config_class = DeepFakeConfig
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classify=True,
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num_classes=1,
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device=config.DEVICE
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)
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DeepFakeConfig.register_for_auto_class()
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DeepFakeModel.register_for_auto_class("AutoModelForImageClassification")
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