Uploaded required 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('plot-classifier-quantized.onnx')
+input_name = inf_session.get_inputs()[0].name
+output_name = inf_session.get_outputs()[0].name
+
+def classify_plot_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_plot_genre, inputs="text", outputs=label)
+iface.launch(inline=False)
+					

genre_types_encoded.json

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

plot-classifier-quantized.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9a53ab874e8570606c46b7cbd2bfe5a8ecbc3c5c20800b8a5e8a0c8e6277c740
+size 82481413

requirements.txt

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+gradio==3.17.0
+onnxruntime==1.14.0
+torch==1.13.1
+transformers==4.26.0