The data for each set is likely stored in a standard format such as . Loading it with Python's pandas library is straightforward:
: Data from WALS is often exported for machine learning. Researchers might use "Sets" of linguistic features (e.g., word order, consonant inventories) to train models like RoBERTa to understand cross-linguistic patterns. Software Archives WALS Roberta Sets 1-36.zip
RoBERTa (Robustly Optimized BERT Approach) is a transformers model pre‑trained on a large corpus of English data in a self‑supervised fashion. It builds on the BERT architecture but uses improved training methods (e.g., dynamic masking, larger batch sizes, more data) to achieve state‑of‑the‑art performance on many NLP tasks. The data for each set is likely stored