update ui

app.py

@@ -25,9 +25,9 @@ def predict(input_str, model_name, progress=gr.Progress()):
 
     if type(output_sentences[0]) == list:
         detok = TreebankWordDetokenizer()
-        return "<br>".join([detok.detokenize(recombine_tokens(sent)) for sent in output_sentences])
+        return "\n".join([detok.detokenize(recombine_tokens(sent)) for sent in output_sentences])
     else:
-        return "<br>".join(output_sentences)
+        return "\n".join(output_sentences)
 
 def predict_transnormer(tokenized_sentences, progress):
     model_name = 'ybracke/transnormer-19c-beta-v02'
@@ -117,8 +117,8 @@ def predict_type_transformer_with_lm(tokenized_sentences, progress):
 
 gradio_app = gr.Interface(
     predict,
-    inputs=[gr.Textbox(value="Die Königinn ſaß auf des Pallaſtes mittlerer Tribune."), gr.Dropdown([('aehrm/dtaec-type-normalizer (FAST)', 'type normalizer'), ('aehrm/dtaec-type-normalizer + dbmdz/german-gpt2 (Fast)', 'type normalizer + lm'), ('ybracke/transnormer-19c-beta-v02 (fast)', 'transnormer')])],
-    outputs=gr.HTML(),
+    inputs=[gr.Textbox(label="Input", value="Die Königinn ſaß auf des Pallaſtes mittlerer Tribune."), gr.Dropdown([('aehrm/dtaec-type-normalizer (FAST)', 'type normalizer'), ('aehrm/dtaec-type-normalizer + dbmdz/german-gpt2 (Fast)', 'type normalizer + lm'), ('ybracke/transnormer-19c-beta-v02 (fast)', 'transnormer')], label="Model")],
+    outputs=gr.Textbox(label="Output", show_label=True),
     title="German Historical Text Normalization",
 )