slight tweaks to code and README

README.md

@@ -11,7 +11,7 @@ pinned: false
 Project for CS-GY-6613 Spring 2023
 
 # Milestone 3
-USPTO Patentability Classifier:https://huggingface.co/spaces/dbleek/cs-gy-6613-project
+USPTO Patentability Classifier:https://huggingface.co/spaces/dbleek/cs-gy-6613-project-final
 
 # Milestone 2
 Sentiment Analysis App:https://huggingface.co/spaces/dbleek/cs-gy-6613-project

milestone-3.py

@@ -31,7 +31,6 @@ dataset = dataset.sort("patent_number")
 model = torch.load("patent_classifier_v4.pt", map_location=torch.device("cpu"))
 tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
 tokenizer_kwargs = {'padding':True,'truncation':True}
-classifier = pipeline("text-classification", model=model, tokenizer=tokenizer, **tokenizer_kwargs)
 
 def load_data():
     selected_application = dataset.select([applications[st.session_state.id]])
@@ -47,11 +46,10 @@ applications = {}
 for ds_index, example in enumerate(dataset):
     applications.update({example["patent_number"]: ds_index})
 st.selectbox(
-    "Select a sample patent application:", applications, on_change=load_data, key="id"
-)
+    "Select a sample patent application:", applications, on_change=load_data, key="id")
 
 # Sample title/decision displayed for additional context only, not used with model
-st.text_input("Sample Title", key="title", value=dataset[0]["title"])
+st.text_input("Sample Title", key="title", value=dataset[0]["title"],)
 st.text_input("Sample Decision", key="decision", value=dataset[0]["decision"])
 
 # Classifier input form
@@ -72,7 +70,7 @@ if submitted:
     pred = torch.softmax(logits, dim=1)
     score = pred[0][1] # index 1 of softmax output is probability that decision = ACCEPTED
     st.markdown(
-        "This application's patentability score is  **{}**".format(score)
+        "This application's patentability score is  **{}**.".format(score)
     )