Update app.py

app.py

@@ -5,7 +5,7 @@ def install(package):
     subprocess.check_call([sys.executable, "-m", "pip", "install", package])
 
 install("transformers")
-# install("torch")
+install("torch")
 install("sentencepiece")
 install("gradio")
 
@@ -19,12 +19,12 @@ from transformers.models.auto.tokenization_auto import AutoTokenizer
 model_name = "deepset/tinyroberta-squad2"  # distilled model: "deepset/tinyroberta-squad2", "deepset/xlm-roberta-base-squad2"
 
 # a) Get predictions
-nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
-QA_input = {
-    'question': 'Why is model conversion important?',
-    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
-}
-res = nlp(QA_input)
+# nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+# QA_input = {
+#    'question': 'Why is model conversion important?',
+#    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
+#}
+#res = nlp(QA_input)
 
 # b) Load model & tokenizer
 model = AutoModelForQuestionAnswering.from_pretrained(model_name)