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vit-gpt2-stablediffusion2-lora

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vision-encoder-decoder
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@@ -29,7 +29,7 @@ It produces optimal results in a reasonable time. Moreover, its implementation w
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  from transformers import ViTFeatureExtractor, AutoTokenizer, VisionEncoderDecoderModel
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  # Model
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- model_id = "nttdataspain/vit-gpt2-coco-lora"
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  model = VisionEncoderDecoderModel.from_pretrained(model_id)
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  tokenizer = AutoTokenizer.from_pretrained(model_id)
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  feature_extractor = ViTFeatureExtractor.from_pretrained(model_id)
 
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  from transformers import ViTFeatureExtractor, AutoTokenizer, VisionEncoderDecoderModel
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  # Model
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+ model_id = "nttdataspain/vit-gpt2-stablediffusion2-lora"
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  model = VisionEncoderDecoderModel.from_pretrained(model_id)
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  tokenizer = AutoTokenizer.from_pretrained(model_id)
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  feature_extractor = ViTFeatureExtractor.from_pretrained(model_id)