clf = RandomForestClassifier() clf.fit(X, y) print("Accuracy on set1:", clf.score(X_test, y_test))
Extracting the archive would likely reveal: WALS Roberta Sets 1-36.zip
: RoBERTa uses Masked Language Modeling (MLM) , where it is trained to predict missing words in a sentence by looking at the context before and after the "mask". clf = RandomForestClassifier() clf
One of the most powerful uses of is transferring predictions to languages not in WALS. Because RoBERTa learns from subword tokens, you can: clf = RandomForestClassifier() clf.fit(X
While this exact zip file is often found on niche download mirrors and forums, its components typically serve the following purposes in computational linguistics: Linguistic Typology Mapping