Create app.py

app.py

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+import gradio as gr
+import onnxruntime 
+from transformers import AutoTokenizer
+import torch, json
+
+token = AutoTokenizer.from_pretrained('pablocosta/bertabaporu-large-uncased')
+
+with open("genre_types_encoded.json", "r") as fp:
+  types = json.load(fp)
+
+types = list(types)
+
+
+inf_session = onnxruntime.InferenceSession('https://drive.google.com/file/d/1-8Iru2d_NjNmZ_czxu87IjIX1meBea4E/view?usp=sharing')
+input_name = inf_session.get_inputs()[0].name
+output_name = inf_session.get_outputs()[0].name
+
+def classify(review):
+    input_ids = token(review)['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(types, map(float, probs))) 
+
+
+label = gr.outputs.Label(num_top_classes=5)
+iface = gr.Interface(fn=classify, inputs="text", outputs=label)
+iface.launch(inline=False)