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Enrich Open Measures Fediverse with Datastreamer Cultural Reference Recognition Model
Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
About Open Measures Fediverse
Collect from a subset of instances that Open Measures users have identified as dangerous or worth investigating. From there, Open Measures crawl these instances for posts and user profiles, while identifying the Fediverse site where the content was posted.
About Datastreamer Cultural Reference Recognition Model
Movies, songs, memes, books, and other cultural references can be detected with this LLM-powered model in over 200+ languages. This classifier can instantly consume the content within a pipeline, optimize the content for speed and cost efficiency, and pass into LLM systems. Within the classifier, the LLM response is restructured, the post is augmented with the new metadata, and continues in the pipeline.
Quickly enrich Open Measures Fediverse with Datastreamer Cultural Reference Recognition Model with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Open Measures Fediverse
For robust enterprise data integration, web data acts as a foundational source. It can be drawn from a variety of channels—including third-party partners, internal applications, and public web repositories.
Step 2
Add Datastreamer Cultural Reference Recognition Model to enrich
Take your web data further. From enrichment to filtering and everything in between, Datastreamer’s vast library of operations helps you act on your data fast—with no coding required.
Step 3
That's it! You have just connected Open Measures Fediverse and Datastreamer Cultural Reference Recognition Model
Datastreamer takes the pain out of web data workflows. Seamlessly scale your Pipelines and resolve persistent operational challenges with ease.