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jev-dataops

jev-dataops — A lot of people will waste time in both pre training and post training of LLM in general…

jev-dataops is A lot of people will waste time in both pre training and post training of LLM in general domain and domain specific training during data pipeline, and performan. It is ranked #469 on the Dev Radar, in AI dev tools, first seen 1 h ago and shared in 1 post (1.2k views).

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What jev-dataops says about itself

An open-source JEV-powered workbench for streaming data selection, quality evaluation, automatic LoRA training and held-out model evaluation. - RenaGao/jev-dataops

GitHub - RenaGao/jev-dataops: An open-source JEV-powered workbench for streaming data selection, quality evaluation, automatic LoRA training and held-out model evaluation. · GitHub Skip to content Navigation Menu Sign in Appearance settings Search / Sign in Sign up Appearance settings You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert {{ message }} RenaGao / jev-dataops Public Notifications You must be signed in to change notification settings Fork 1…

What people said about jev-dataops on X

DATA! DATA! DATA!

@GenAI_is_real, 1 h ago · 6 likes · see the post

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FAQ

What is jev-dataops?

A lot of people will waste time in both pre training and post training of LLM in general domain and domain specific training during data pipeline, and performan It was first shared on X 1 h ago and is ranked #469 on the Dev Radar.

Is jev-dataops free?

It is open source.

Who shared jev-dataops?

1 account on X, including @GenAI_is_real, in 1 post totalling 1.2k views.

Every post is read and classified by Jev (TypeSafe): what it is, which market it belongs to, and whether the link is a real tool. 17.7k posts from 4.9k X accounts over the last 21 days, 2k tools, 12 markets. Collected every 5 minutes, fully re-ranked every hour — last update 2026-09-21 04:44 UTC. Full method.