beam size 1

app.py

@@ -47,7 +47,7 @@ def predict_transnormer(tokenized_sentences, progress):
     ds = KeyDataset(Dataset.from_dict(dict(types=list(raw_sentences))), "types")
 
     output_sentences = []
-    for out_sentence in progress.tqdm(pipe(ds, num_beams=4, max_length=1024)):
+    for out_sentence in progress.tqdm(pipe(ds, num_beams=1, max_length=1024)):
         output_sentences.append(out_sentence[0]['generated_text'])
 
     return output_sentences