Update README.md (#1)

- Update README.md (eb0cb058b2d16a5122663b03666d0e5ba5683592)

README.md

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 ---
 license: apache-2.0
+datasets:
+- atasoglu/flickr8k-turkish
+language:
+- tr
+metrics:
+- rouge
+library_name: transformers
+pipeline_tag: image-to-text
+tags:
+- image-to-text
+- image-captioning
+base_model:
+- google/vit-base-patch16-224
+- ytu-ce-cosmos/turkish-gpt2
 ---
+
+# vit-base-patch16-224-turkish-gpt2-medium
+
+This vision encoder-decoder model utilizes the [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) as the encoder and [ytu-ce-cosmos/turkish-gpt2-medium](https://huggingface.co/ytu-ce-cosmos/turkish-gpt2-medium) as the decoder, and it has been fine-tuned on the [flickr8k-turkish](https://huggingface.co/datasets/atasoglu/flickr8k-turkish) dataset to generate image captions in Turkish.
+
+## Usage
+
+```py
+import torch
+from transformers import VisionEncoderDecoderModel, ViTImageProcessor, AutoTokenizer
+from PIL import Image
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model_id = "atasoglu/vit-base-patch16-224-turkish-gpt2-medium"
+img = Image.open("example.jpg")
+
+feature_extractor = ViTImageProcessor.from_pretrained(model_id)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = VisionEncoderDecoderModel.from_pretrained(model_id)
+model.to(device)
+
+features = feature_extractor(images=[img], return_tensors="pt")
+pixel_values = features.pixel_values.to(device)
+
+generated_captions = tokenizer.batch_decode(
+    model.generate(pixel_values, max_new_tokens=20),
+    skip_special_tokens=True,
+)
+
+print(generated_captions)
+```