Update README.md

README.md

@@ -10,4 +10,41 @@ widget:
   - src: >-
       https://huggingface.co/snzhang/FileTitle-Beit-GPT2/resolve/main/BorntoFly.jpg
     example_title: Born to Fly
----
+---
+
+# Image Caption Model
+
+## Model description
+
+The model is used to generate the Chinese title of a random movie post. It is based on the [BEiT](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) and [GPT2](https://huggingface.co/IDEA-CCNL/Wenzhong-GPT2-110M).
+
+## Training Data
+
+The training data contains 5043 movie posts and their corresponding Chinese title which are collected by [Movie-Title-Post](https://huggingface.co/datasets/snzhang/Movie-Title-Post)
+
+## How to use
+
+```Python
+from transformers import VisionEncoderDecoderModel, ViTFeatureExtractor, AutoTokenizer
+from PIL import Image
+
+pretrained = "snzhang/FileTitle-Beit-GPT2"
+model = VisionEncoderDecoderModel.from_pretrained(pretrained)
+feature_extractor = ViTFeatureExtractor.from_pretrained(pretrained)
+tokenizer = AutoTokenizer.from_pretrained(pretrained)
+
+image_path = "your image path"
+image = Image.open(image_path)
+if image.mode != "RGB":
+        image = image.convert("RGB")
+pixel_values = feature_extractor(images=image, return_tensors="pt").pixel_values
+
+output_ids = model.generate(pixel_values, **gen_kwargs)
+preds = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
+preds = [pred.strip() for pred in preds]
+print(preds)
+```
+
+## More Details
+
+You can get more training details in [FileTitle-Beit-GPT2](https://github.com/h7nian/FileTitle-Beit-GPT2)