ai-agents-t5-classification-he-typeerror-forward-got-an-unexpected-keyword-argume-f00a1991

THEN To use T5 encoder models for sequence classification, create a custom model by adding a classification head on top of the encoder. Implement the forward method to accept labels, compute cross-entropy loss, and return both loss and logits. Follow the pattern of BertForSequenceClassification.

class T5ForSequenceClassification(nn.Module):
    def __init__(self, model_name, num_labels):
        super().__init__()
        self.encoder = T5EncoderModel.from_pretrained(model_name)
        self.classifier = nn.Linear(self.encoder.config.hidden_size, num_labels)
    def forward(self, input_ids, attention_mask=None, labels=None):
        outputs = self.encoder(input_ids, attention_mask=attention_mask)
        pooled = outputs.last_hidden_state.mean(dim=1)
        logits = self.classifier(pooled)
        loss = None
        if labels is not None:
            loss_fn = nn.CrossEntropyLoss()
            loss = loss_fn(logits, labels)
        return (loss, logits) if loss is not None else logits