Update app.py

app.py

@@ -6,22 +6,22 @@ import torch, json
 tokenizer = AutoTokenizer.from_pretrained("distilroberta-base")
 
 with open("dataset_types_encoded.json", "r") as fp:
-  encode_genre_types = json.load(fp)
+  encode_category_types = json.load(fp)
 
-genres = list(encode_genre_types.keys())
+categories = list(encode_category_types.keys())
 
 inf_session = rt.InferenceSession('dataset-classifier-distilroberta-quantized.onnx')
 input_name = inf_session.get_inputs()[0].name
 output_name = inf_session.get_outputs()[0].name
 
-def classify_dataset_genre(description):
+def classify_dataset_type(description):
   input_ids = tokenizer(description)['input_ids'][:512]
   logits = inf_session.run([output_name], {input_name: [input_ids]})[0]
   logits = torch.FloatTensor(logits)
   probs = torch.sigmoid(logits)[0]
-  return dict(zip(genres, map(float, probs))) 
+  return dict(zip(categories, map(float, probs))) 
 
 label = gr.outputs.Label(num_top_classes=3)
-iface = gr.Interface(fn=classify_book_genre, inputs="text", outputs=label)
+iface = gr.Interface(fn=classify_dataset_type, inputs="text", outputs=label)
 iface.launch(inline=False)