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return features.detach().numpy()
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.
# Forward pass outputs = model(**inputs)
# Load pre-trained model and tokenizer model_name = "distilbert-base-uncased" model = AutoModel.from_pretrained(model_name) tokenizer = AutoTokenizer.from_pretrained(model_name)
return features.detach().numpy()
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. www.moviehdkh
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
# Forward pass outputs = model(**inputs) www.moviehdkh
# Load pre-trained model and tokenizer model_name = "distilbert-base-uncased" model = AutoModel.from_pretrained(model_name) tokenizer = AutoTokenizer.from_pretrained(model_name)

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