| ## Bert-base-uncased for Android-Ios Question Classification |
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| **Code**: See [Ainize Workspace](https://ainize.ai/workspace/create?imageId=hnj95592adzr02xPTqss&git=https://github.com/EastHShin/Android-Ios-Classification-Workspace) |
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| **Android-Ios-Classification DEMO**: [Ainize Endpoint](https://main-android-ios-classification-east-h-shin.endpoint.ainize.ai/) |
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| **Demo web Code**: [Github](https://github.com/EastHShin/Android-Ios-Classification) |
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| **Android-Ios-Classification API**: [Ainize API](https://ainize.ai/EastHShin/Android-Ios-Classification) |
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| ## Overview |
| **Language model**: bert-base-cased |
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| **Language**: English |
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| **Training data**: Question classification Android-Ios dataset from [Kaggle](https://www.kaggle.com/xhlulu/question-classification-android-or-ios) |
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| ## Usage |
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| ``` |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline |
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| model_path = "EasthShin/Android_Ios_Classification" |
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| tokenizer = AutoTokenizer.from_pretrained(model_path) |
| model = AutoModelForSequenceClassification.from_pretrained(model_path) |
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| classifier = pipeline('text-classification', model=model_path, tokenizer=tokenizer) |
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| question = "I bought goodnote in Appstore" |
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| result = dict() |
| result[0] = classifier(question)[0] |
| ``` |
