Fine Tuning LLMs to Process Massive Amounts of Data 50x Cheaper than GPT-4

This page summarizes the projects mentioned and recommended in the original post on dev.to

SurveyJS - Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App
With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.
surveyjs.io
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InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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  • OpenPipe

    Turn expensive prompts into cheap fine-tuned models

  • In this article I'll share how I used OpenPipe to effortlessly fine tune Mistral 7B, reducing the cost of one of my prompts by 50x. I included tips and recommendations if you are doing this for the first time, because I definitely left some performance increases on the table. Skip to Fine Tuning Open Recommender if you are specifically interested in what the fine tuning process looks like. You can always DM me on Twitter (@experilearning) or leave a comment if you have questions!

  • open-recommender

    Discontinued Using LLMs to implement an open source YouTube video recommendation system. [Moved to: https://github.com/OpenPipe/open-recommender] (by bjsi)

  • Over the past month I have been working on Open Recommender, an open source YouTube video recommendation system which takes your Twitter feed as input and recommends you relevant YouTube-shorts style video clips.

  • SurveyJS

    Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.

    SurveyJS logo
NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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