Update README.md

README.md

@@ -30,7 +30,7 @@ example_sentence = "Anvpreiſungq. Haupidepot für Wien: In der Stadt, obere Br
 tokenizer = AutoTokenizer.from_pretrained("Var3n/hmByT5_anno")
 model = AutoModelForSeq2SeqLM.from_pretrained("Var3n/hmByT5_anno")
 
-input = tokenizer(input, return_tensors="pt").input_ids
+input = tokenizer(example_sentence, return_tensors="pt").input_ids
 output = model.generate(input, max_new_tokens=len(input[0]), num_beams=4, do_sample=True)
 
 text = tokenizer.decode(output[0], skip_special_tokens=True)