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# Using BEiT-3 to get text-vision embedding
## For text embedding
1. Create file ```test_model.py``` inside folder ```itr```.
2. Using the code follow:
```
from beit3_model import Beit3Model
if __name__ == '__main__':
vlm = Beit3Model(device='cpu')
print(vlm.get_embedding('A man who loves a girl.').shape)
```
## For image embedding
1. Create file ```test_model.py``` inside folder ```itr```.
2. Using the code follow:
```
from beit3_model import Beit3Model
from torchvision.datasets.folder import default_loader
if __name__ == '__main__':
loader = default_loader
image = loader('./path/to/your/image.jpg')
vlm = Beit3Model(device='cpu')
print(vlm.get_embedding(image).shape)
``` |