Update app.py

app.py

@@ -73,11 +73,23 @@ model_id_7 = "oliverguhr/german-sentiment-bert"
 
 from transformers import pipeline
 
-pipe = pipeline("sentiment", model=model_id_7)
+# 
+##
+#"['audio-classification', 'automatic-speech-recognition', 'conversational', 'depth-estimation', 'document-question-answering', 
+#'feature-extraction', 'fill-mask', 'image-classification', 'image-segmentation', 'image-to-text', 'mask-generation', 'ner', 
+#'object-detection', 'question-answering', 'sentiment-analysis', 'summarization', 'table-question-answering', 'text-classification', 
+#'text-generation', 'text2text-generation', 'token-classification', 'translation', 'video-classification', 'visual-question-answering', 
+#'vqa', 'zero-shot-audio-classification', 'zero-shot-classification', 'zero-shot-image-classification', 'zero-shot-object-detection', 
+#'translation_XX_to_YY']"
+##
+
+pipe = pipeline("sentiment-analysis", model=model_id_7)
 #pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-en-es")
 
 def predict(text):
-  return pipe(text)[0]["translation_text"]
+  sentiment_result = pipe(text)[0]["sentiment_text"]
+  print(sentiment_result)
+  return sentiment_result
 
 demo = gr.Interface(
   fn=predict,