Create README.md

README.md

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+---
+metrics:
+- bleu
+- rouge
+tags:
+- image-to-text
+- image-captioning
+- vision-transformer
+- ViT-B/16
+language:
+- id
+- en
+---
+
+# Sample running code
+```python
+from transformers import VisionEncoderDecoderModel, ViTImageProcessor, GPT2Tokenizer
+import torch
+from PIL import Image
+model = VisionEncoderDecoderModel.from_pretrained("evlinzxxx/my_model_ViTB-16")
+feature_extractor = ViTImageProcessor.from_pretrained("evlinzxxx/my_model_ViTB-16")
+tokenizer = GPT2Tokenizer.from_pretrained("evlinzxxx/my_model_ViTB-16")
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+def show_image_and_captions(url):
+  # get the image and display it
+  display(load_image(url))
+  # get the captions on various models
+  our_caption = get_caption(model, image_processor, tokenizer, url)
+  # print the captions
+  print(f"Our caption: {our_caption}")
+show_image_and_captions("/content/drive/MyDrive/try/test_400/gl_16.jpg") # ['navigate around the obstacle ahead adjusting your route to bypass the parked car.']
+```