clean up app.py

app.py

@@ -6,6 +6,7 @@ from uq import BertForUQSequenceClassification
 def predict(sentence):
     model_path = "tombm/bert-base-uncased-finetuned-cola"
     classifier = pipeline("text-classification", model=model_path, tokenizer=model_path)
+    set_seed(12)
     label = classifier(sentence)[0]["label"]
     return label
 
@@ -15,6 +16,7 @@ def uncertainty(sentence):
     tokenizer = AutoTokenizer.from_pretrained(model_path)
     model = BertForUQSequenceClassification.from_pretrained(model_path)
 
+    set_seed(12)
     test_input = tokenizer(sentence, return_tensors="pt")
     model.return_gp_cov = True
     _, gp_cov = model(**test_input)
@@ -23,7 +25,6 @@ def uncertainty(sentence):
 
 
 with gr.Blocks() as demo:
-    set_seed(12)
     intro_str = """The *cola* dataset focuses on determining whether sentences are grammatically correct.
                Firstly, let's see how our finetuned model classifies two sentences, 
                the first of which is correct (i.e. valid) and the second is not (i.e. invalid):"""
@@ -66,5 +67,3 @@ with gr.Blocks() as demo:
     gr.Markdown(value=final_str)
 
 demo.launch()
-# iface = gr.Interface(fn=predict, inputs="text", outputs="text")
-# iface.launch()