Www.moviehdkh 【360p 2024】

# Example usage text_data = ["This is a great movie!", "I loved the action scenes."] features = [extract_text_features(text) for text in text_data]

To extract deep features, we can consider the following approaches:

# Load pre-trained model and tokenizer model_name = "distilbert-base-uncased" model = AutoModel.from_pretrained(model_name) tokenizer = AutoTokenizer.from_pretrained(model_name)

Make sure to check the website's terms of use and robots.txt file (e.g., www.moviehdkh/robots.txt) before scraping or crawling the website.

print(features) This example uses a pre-trained DistilBERT model to extract features from text data. You'll need to adapt this code to your specific use case and data.

return features.detach().numpy()

import pandas as pd from transformers import AutoModel, AutoTokenizer import torch

def extract_text_features(text): # Tokenize text inputs = tokenizer(text, return_tensors="pt")