| Load DistilBERT with [AutoModelForTokenClassification] along with the number of expected labels, and the label mappings: | |
| from transformers import AutoModelForTokenClassification, TrainingArguments, Trainer | |
| model = AutoModelForTokenClassification.from_pretrained( | |
| "distilbert/distilbert-base-uncased", num_labels=13, id2label=id2label, label2id=label2id | |
| ) | |
| At this point, only three steps remain: | |
| Define your training hyperparameters in [TrainingArguments]. |