Here's an example using scikit-learn:
print(X.toarray()) The resulting matrix X can be used as a deep feature for the text. part 1 hiwebxseriescom hot
tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased') model = AutoModel.from_pretrained('bert-base-uncased') Here's an example using scikit-learn: print(X
from sklearn.feature_extraction.text import TfidfVectorizer I can suggest a few approaches:
Using a library like Gensim or PyTorch, we can create a simple embedding for the text. Here's a PyTorch example:
Assuming you want to create a deep feature for the text "hiwebxseriescom hot", I can suggest a few approaches: