| ## Bert-base-uncased for Android-Ios Question Classification | |
| **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/) | |
| <br> | |
| **Demo web Code**: [Github](https://github.com/EastHShin/Android-Ios-Classification) | |
| <br> | |
| **Android-Ios-Classification API**: [Ainize API](https://ainize.ai/EastHShin/Android-Ios-Classification) | |
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| <br> | |
| ## 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) | |
| ## Usage | |
| ``` | |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline | |
| model_path = "EasthShin/Android_Ios_Classification" | |
| tokenizer = AutoTokenizer.from_pretrained(model_path) | |
| model = AutoModelForSequenceClassification.from_pretrained(model_path) | |
| classifier = pipeline('text-classification', model=model_path, tokenizer=tokenizer) | |
| question = "I bought goodnote in Appstore" | |
| result = dict() | |
| result[0] = classifier(question)[0] | |
| ``` |