🚨 Train Your Own LLM Using A Text Prompt - start with a text prompt - customize based on your use-case - run LLMs locally Try it on Abacus AI SuperComputer

does training optimize for the local machine's memory limit, even when that costs task accuracy?

Looks cool

your rules in a small model beats scale

Slick demo. How can I try it

But what about the data, top tech firms has huge amount of data to train😥

What does "run LLMs locally" need hardware-wise, one box or the supercomputer?

Slick demo but the VRAM bill is the real story

This is the part I used to skip, because a prompt that spins up a model feels like the whole win. I learned the hard way that the local run is where my assumptions get tested, because a model that only works on a demo machine is not really mine yet.

A prompt that spins up a local model is a nice on-ramp. The part that still decides if it is usable is eval: you need a way to notice when the custom weights got worse.

People in these comments have no idea the potential this unlockes!

This is amazing

The prompt-to-model part is neat, but the data is still the hard part. In a niche like SEO, a small model trained on your own audits and client notes will beat a big general one on that exact task. Curious how it handles cleaning the training data, since that's where most custom models go wrong.

prompt-to-model. fine-tuning just became a text box

training your own LLM from a prompt is wild

What’s an LLm tuhistessa

what base model is underneath?

Kr de bhai.. aaj hi krde.. atleast skip Ni krna pdega tera screen time

👍👍

Cool demo — question on the mechanics: do the text prompts get compiled into synthetic training data via a teacher model, or do they steer fine-tuning more directly? Wondering how a few prompts avoid collapsing into a narrow distribution.

Running and customizing LLMs locally is getting more accessible every day. exciting times for builders