adding model classification

app.py

@@ -1,9 +1,27 @@
 import gradio as gr
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoConfig
+import json
 
+with open("tag_map.json") as tag_map_file:
+    tag_map = json.load(tag_map_file)
 
-def greet(name):
-    return "Hello " + name + "!!"
+reverse_map = {j: i for i, j in tag_map.items()}
 
+model_name_or_path = "roberta-base"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+config = AutoConfig.from_pretrained(model_name_or_path)
+config.num_classes = len(tag_map)
+model = AutoModelForSequenceClassification.from_pretrained(
+    model_name_or_path, config=config
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
+
+
+def classify(text):
+    return reverse_map[
+        model(**tokenizer(text, return_tensors="pt")).logits.argmax(-1).item()
+    ]
+
+
+iface = gr.Interface(fn=classify, inputs="text", outputs="text")
 iface.launch()

tag_map.json

@@ -0,0 +1 @@
+{"advantageous_effects_of_the_invention": 0, "solution_to_the_problem": 1, "technical_problem": 2, "other": 3}