Rimi98/NegativeCommentClassifier

1import gradio as gr2import onnxruntime 3from transformers import AutoTokenizer4import torch, json5 6token = AutoTokenizer.from_pretrained('distilroberta-base')7 8types = ['Toxic','Severe_toxic','Obscene','Threat','Insult','Identity_hate']9 10inf_session = onnxruntime.InferenceSession('classifier-quantized.onnx')11input_name = inf_session.get_inputs()[0].name12output_name = inf_session.get_outputs()[0].name13 14def classify(review):15    input_ids = token(review)['input_ids'][:512]16    logits = inf_session.run([output_name], {input_name: [input_ids]})[0]17    logits = torch.FloatTensor(logits)18    probs = torch.sigmoid(logits)[0]19    return dict(zip(types, map(float, probs))) 20 21 22label = gr.outputs.Label(num_top_classes=5)23iface = gr.Interface(fn=classify, inputs="text", outputs=label)24iface.launch(inline=False)