Hnabil
/

t5-address-standardizer

text2text-generation

text-generation-inference

Model card Files Files and versions

Hnabil commited on Jun 15, 2023

Commit

fdc49e8

·

1 Parent(s): c4c0f74

Update README.md

Files changed (1) hide show

README.md +4 -1

README.md CHANGED Viewed

@@ -22,7 +22,10 @@ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 model = AutoModelForSeq2SeqLM.from_pretrained("Hnabil/t5-address-standardizer")
 tokenizer = AutoTokenizer.from_pretrained("Hnabil/t5-address-standardizer")
-inputs = tokenizer("220, soyth rhodeisland aveune, mason city, iowa, 50401, us", return_tensors="pt")
 outputs = model.generate(**inputs, max_length=100)
 print(tokenizer.batch_decode(outputs, skip_special_tokens=True))

 model = AutoModelForSeq2SeqLM.from_pretrained("Hnabil/t5-address-standardizer")
 tokenizer = AutoTokenizer.from_pretrained("Hnabil/t5-address-standardizer")
+inputs = tokenizer(
+  "220, soyth rhodeisland aveune, mason city, iowa, 50401, us",
+  return_tensors="pt"
+)
 outputs = model.generate(**inputs, max_length=100)
 print(tokenizer.batch_decode(outputs, skip_special_tokens=True))