adding files

app.py

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+import gradio as gr
+import onnxruntime as rt
+from transformers import AutoTokenizer
+import torch, json
+
+tokenizer = AutoTokenizer.from_pretrained("distilroberta-base")
+
+with open("genre_types_encoded.json", "r") as fp:
+  encode_genre_types = json.load(fp)
+
+genres = list(encode_genre_types.keys())
+
+inf_session = rt.InferenceSession('movie_gnere-classifier-quantized.onnx')
+input_name = inf_session.get_inputs()[0].name
+output_name = inf_session.get_outputs()[0].name
+
+def classify_book_genre(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))) 
+
+label = gr.outputs.Label(num_top_classes=5)
+iface = gr.Interface(fn=classify_book_genre, inputs="text", outputs=label)
+iface.launch(inline=False)
+					

genre_types_encoded.json

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+{"Action": 0, "Adventure": 1, "Drama": 2, "Comedy": 3, "Thriller": 4, "Mystery": 5, "Family": 6, "Fantasy": 7, "Romance": 8, "Biography": 9, "History": 10, "Sport": 11, "Crime": 12, "Musical": 13, "Sci-fi": 14, "Horror": 15, "Animation": 16, "Music": 17, "War": 18, "Documentary": 19, "Western": 20}

movie_gnere-classifier-quantized.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7dfa4f9cce8138fee42090760ec87fdb0e7139b23574fcd51e5b2e092cae5d66
+size 82573551