Create README.md

README.md

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+model_name = 'logicreasoning/LogiT5'
+tokenize = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+device = 'cuda:0' if torch.cuda.is_available() else 'cpu'
+input_text = '' #your input text here
+input = tokenize(input, return_tensors='pt', padding=True).to(device)
+model = model.to(device)
+output = model.generate(*input, max_length=1024)
+prediction = tokenize.decode(output[0],skip_special_tokens=True)