+34 91 416 55 11

tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased') model = AutoModel.from_pretrained('bert-base-uncased')

from sklearn.feature_extraction.text import TfidfVectorizer

text = "hiwebxseriescom hot"

vectorizer = TfidfVectorizer() X = vectorizer.fit_transform([text])

Here's an example using scikit-learn:

Part 1 Hiwebxseriescom Hot «VALIDATED»

tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased') model = AutoModel.from_pretrained('bert-base-uncased')

from sklearn.feature_extraction.text import TfidfVectorizer part 1 hiwebxseriescom hot

text = "hiwebxseriescom hot"

vectorizer = TfidfVectorizer() X = vectorizer.fit_transform([text]) tokenizer = AutoTokenizer

Here's an example using scikit-learn: