Filmtitle Beit GPT2

🚀 Image Caption Model

This model is designed to generate Chinese titles for random movie posters, leveraging the power of BEiT and GPT2.

🚀 Quick Start

This model is used to generate the Chinese title of a random movie post. It combines the capabilities of BEiT and GPT2.

✨ Features

• Generate Chinese titles for movie posters.
• Based on the BEiT and GPT2 models.

📦 Installation

No specific installation steps are provided in the original README.

💻 Usage Examples

Basic Usage

from transformers import VisionEncoderDecoderModel, ViTFeatureExtractor, AutoTokenizer
from PIL import Image

pretrained = "snzhang/FilmTitle-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)

📚 Documentation

Training Data

The training data contains 5043 movie posts and their corresponding Chinese title which are collected by Movie-Title-Post

More Details

You can get more training details in FilmTitle-Beit-GPT2

📄 License

This project is licensed under the Apache-2.0 license.