Instructions to use not-lain/deepfake with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use not-lain/deepfake with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="not-lain/deepfake", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("not-lain/deepfake", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
commit files to HF hub
Browse files- deepfakemodel.py +1 -1
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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class DeepFakeModel(PreTrainedModel):
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config_class = DeepFakeConfig
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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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