controllers/test_folders/models/language_model.py

import torch
from transformers import AutoModelForSequenceClassification, AutoTokenizer

class LanguageModel:
    def __init__(self):
        self.model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased")
        self.tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")

    def predict(self, text, image):
        # For simplicity, let's assume the image is not used in this example
        inputs = self.tokenizer.encode_plus(
            text,
            add_special_tokens=True,
            max_length=512,
            return_attention_mask=True,
            return_tensors='pt'
        )
        outputs = self.model(inputs['input_ids'], attention_mask=inputs['attention_mask'])
        return torch.argmax(outputs.logits)