# Add padding tokens to match the expected dimensions # This prevents the 'IndexError' during the batch collation. tokenizer.add_tokens([f"<wals_extra_i>" for i in range(wals_vocab_size)])

Before diving into the fix, it is crucial to understand what this file contains. The wals_roberta_sets_136.zip archive is typically a collection of:

Run a simple script to verify that your data flows through the neural network pipeline smoothly. Ensure that model(tokenizer(text)) returns full logit dimensions without raising IndexError or ValueError exceptions. Once the validation steps finish, the multi-lingual datasets can be safely used for pre-training or fine-tuning tasks.