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on
Zero
Running
on
Zero
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) |