Update README.md

README.md

@@ -43,20 +43,20 @@ This model currently needs a custom wrapper from `modeling_nort5.py`, you should
 import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-tokenizer = AutoTokenizer.from_pretrained("ltg/nort5-base")
-t5 = AutoModelForSeq2SeqLM.from_pretrained("ltg/nort5-base")
+tokenizer = AutoTokenizer.from_pretrained("ltg/nort5-base", trust_remote_code=True)
+model = AutoModelForSeq2SeqLM.from_pretrained("ltg/nort5-base", trust_remote_code=True)
 
 
 # MASKED LANGUAGE MODELING
 
-sentence = "Brukseksempel: Elektrisk oppvarming. Definisjonen på ordet oppvarming er[MASK_0]."
+sentence = "Brukseksempel: Elektrisk oppvarming. Definisjonen på ordet oppvarming er: å[MASK_0]."
 encoding = tokenizer(sentence)
 
 input_tensor = torch.tensor([encoding.input_ids])
 output_tensor = model.generate(input_tensor, decoder_start_token_id=7, eos_token_id=8)
 tokenizer.decode(output_tensor.squeeze(), skip_special_tokens=True)
 
-# should output:  å varme opp
+# should output: ' varme opp et rom.'
 
 
 # PREFIX LANGUAGE MODELING