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@@ -31,12 +31,12 @@ You can use the raw model for either feature extractor or (un) conditional image
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  Here is how to use this model in PyTorch to perform unconditional image generation:
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  ```python
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- from transformers import ImageGPTFeatureExtractor, ImageGPTForCausalImageModeling
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  import torch
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  import matplotlib.pyplot as plt
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  import numpy as np
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- feature_extractor = ImageGPTFeatureExtractor.from_pretrained('openai/imagegpt-small')
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  model = ImageGPTForCausalImageModeling.from_pretrained('openai/imagegpt-small')
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  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
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  Here is how to use this model in PyTorch to perform unconditional image generation:
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  ```python
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+ from transformers import ImageGPTImageProcessor, ImageGPTForCausalImageModeling
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  import torch
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  import matplotlib.pyplot as plt
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  import numpy as np
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+ feature_extractor = ImageGPTImageProcessor.from_pretrained('openai/imagegpt-small')
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  model = ImageGPTForCausalImageModeling.from_pretrained('openai/imagegpt-small')
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  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")