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Update README.md

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@@ -42,7 +42,7 @@ After, refer the path to OFA-large to `ckpt_dir`, and prepare an image for the t
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  >>> patch_img = patch_resize_transform(img).unsqueeze(0)
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- >>> # using the generator of fairseq version
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  >>> model = OFAModel.from_pretrained(ckpt_dir, use_cache=True)
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  >>> generator = sequence_generator.SequenceGenerator(
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  tokenizer=tokenizer,
@@ -56,7 +56,7 @@ After, refer the path to OFA-large to `ckpt_dir`, and prepare an image for the t
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  >>> gen_output = generator.generate([model], data)
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  >>> gen = [gen_output[i][0]["tokens"] for i in range(len(gen_output))]
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- >>> # using the generator of huggingface version
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  >>> model = OFAModel.from_pretrained(ckpt_dir, use_cache=False)
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  >>> gen = model.generate(inputs, patch_images=patch_img, num_beams=5, no_repeat_ngram_size=3)
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  >>> patch_img = patch_resize_transform(img).unsqueeze(0)
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+ # using the generator of fairseq version
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  >>> model = OFAModel.from_pretrained(ckpt_dir, use_cache=True)
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  >>> generator = sequence_generator.SequenceGenerator(
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  tokenizer=tokenizer,
 
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  >>> gen_output = generator.generate([model], data)
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  >>> gen = [gen_output[i][0]["tokens"] for i in range(len(gen_output))]
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+ # using the generator of huggingface version
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  >>> model = OFAModel.from_pretrained(ckpt_dir, use_cache=False)
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  >>> gen = model.generate(inputs, patch_images=patch_img, num_beams=5, no_repeat_ngram_size=3)
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