![]() This dataset contains over 300k news articles, which makes it a good dataset to build the Searcher model, and return various related news during model inference for a text query. This tutorial uses the publicly available CNN/DailyMail non-anonymized summarization dataset, which was produced from the GitHub repo. Text search using Scalable Nearest Neighbor You can try with your own dataset with the compatible input comma separated value (CSV) format. This tutorial leverages CNN/DailyMail dataset as an instance to create the TFLite Searcher model. ![]() Android) using Task Library Searcher API to run inference with just a few lines of code. After building this, you can deploy it onto devices (e.g. The model returns a list of the smallest distance scoring entries in the dataset, including metadata you specify, such as URL, page title, or other text entry identifiers. This type of model lets you take a text query and search for the most related entries in a text dataset, such as a database of web pages. You can use a text Searcher model to build Sematic Search or Smart Reply for your app. In this colab notebook, you can learn how to use the TensorFlow Lite Model Maker library to create a TFLite Searcher model.
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