Update app.py

app.py

@@ -1,15 +1,21 @@
 import gradio as gr
-from transformers import AutoModelForSequenceClassification, AutoModel, AutoTokenizer
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
 import torch
 from peft import PeftModel, PeftConfig
 
 base_model = "cardiffnlp/twitter-roberta-base-sentiment-latest"
 adapter_model = 'saideep-arikontham/twitter-roberta-base-sentiment-latest-trump-stance'
 
+# define label maps
+id2label = {0: "Anti-Trump", 1 : "Pro-Trump"}
+label2id = {"Anti-Trump" : 0, "Pro-Trump" : 1}
+
+# generate classification model from model_checkpoint
+model = AutoModelForSequenceClassification.from_pretrained(base_model, num_labels=2, id2label = id2label, label2id = label2id, ignore_mismatched_sizes=True)
+
 model = PeftModel.from_pretrained(model, adapter_model)
 tokenizer = AutoTokenizer.from_pretrained(adapter_model)
 
-
 def greet(text):
     
     model.to('mps')
@@ -22,5 +28,6 @@ def greet(text):
     return "This text is " + id2label[predictions.tolist()] + "!!"
 
 
+
 demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo.launch()