# Initialize BERT model and tokenizer for text tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') text_model = BertModel.from_pretrained('bert-base-uncased')
def get_vision_features(image_path): # Load and preprocess the image img = ... # Load image img_t = torch.unsqueeze(img, 0) # Add batch dimension with torch.no_grad(): outputs = vision_model(img_t) return outputs # Features from the last layer busty mature cam
import torch from torchvision import models from transformers import BertTokenizer, BertModel # Initialize BERT model and tokenizer for text
# Initialize a pre-trained ResNet model for vision tasks vision_model = models.resnet50(pretrained=True) busty mature cam
