| import torch |
| from transformers import AdamW, AutoTokenizer, AutoModelForSequenceClassification |
|
|
| # Same as before |
| checkpoint = "bert-base-uncased" |
| tokenizer = AutoTokenizer.from_pretrained(checkpoint) |
| model = AutoModelForSequenceClassification.from_pretrained(checkpoint) |
| sequences = [ |
| "I've been waiting for a HuggingFace course my whole life.", |
| "This course is amazing!", |
| ] |
| batch = tokenizer(sequences, padding=True, truncation=True, return_tensors="pt") |
|
|
| # This is new |
| batch["labels"] = torch.tensor([1, 1]) |
|
|
| optimizer = AdamW(model.parameters()) |
| loss = model(**batch).loss |
| loss.backward() |
| optimizer.step() |
