推出 TextCLF：一个用于创建自定义文本分类模型的 API
大家好！我正在推出 TextCLF：一个允许用户使用自己的数据训练自定义文本分类模型的 API。<p>它可以在 RapidAPI 上使用： https://rapidapi.com/textclf-textclf-default/api/textclf1<p>用户可以使用 TextCLF 和他们的标记数据集来训练用于各种文本分类任务的自定义模型，例如情感分析、文档分类或任何其他涉及文本输入分类的任务。<p>TextCLF 轻量、准确且训练速度快！它将帮助用户创建符合特定需求的自定义文本分类模型。<p>在训练或预测过程中不会保存任何数据。用户可以选择将训练好的模型保存到远程服务器（以便更快的预测），或将模型保存在本地（以确保最大隐私），或者两者都选择。<p>欢迎尝试，并告诉我您的想法以及您对准确度的满意程度！
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Hello All! I’m launching TextCLF: an API that allow users to train custom text classification models with their own data.<p>It’s available on RapidAPI: https://rapidapi.com/textclf-textclf-default/api/textclf1<p>Users can use TextCLF with their labeled dataset to train custom models for a variety of text classification tasks such as sentiment analysis or document classification or any other task that involves classifying with text inputs.<p>TextCLF is lightweight, accurate and fast to train! It will help users create custom text classification models for their specific needs.<p>No data is saved during training or prediction. The user can choose to either save their trained model the remote server (for faster prediction) or save the model locally (for maximum privacy) or both.<p>You can try it and let me know what you think and if you are happy with the accuracy!