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best_model_ViTB16_GPT2
evlinzxxx/best_model_ViTB16_GPT2
best_model_ViTB16_GPT2 is a image-to-text model from evlinzxxx. Use it when you need a caption or text from an image. It is set up for transformers.
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At a glance
- Task
- Image-to-Text
- Library
- transformers
- Model type
- vision-encoder-decoder
- Access
- Public
- Created
- May 19, 2024
- Updated
- May 19, 2024
- SHA
- 76816e00
Model card
From the Hugging Face model README
Sample running code
from transformers import VisionEncoderDecoderModel, ViTImageProcessor, GPT2Tokenizer
import torch
from PIL import Image
model = VisionEncoderDecoderModel.from_pretrained("evlinzxxx/best_model_ViTB16_GPT2")
feature_extractor = ViTImageProcessor.from_pretrained("evlinzxxx/best_model_ViTB16_GPT2")
tokenizer = GPT2Tokenizer.from_pretrained("evlinzxxx/best_model_ViTB16_GPT2")
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.']
- Task
- Image-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- Languages
- id, en
- Created
- May 19, 2024
- Updated
- May 19, 2024