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Revolutionizing Move Programming with OpenLedger In this demo, we showcase how Move datasets contributed by data providers to OpenLedger’s datanets are used to fine-tune specialized models with LoRA fine-tuning. As seen in the video, we showcase an example on how builders can deploy a Move-specialized model that powers Co-pilot...

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OpenLedger

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61,662 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 9

Фото профиля rushi
rushi1 год назад

AI MOVE

Фото профиля UserInterface
UserInterface2 лет назад

How to Make Sales on UserInterface Freelance Marketplace #freelance

Фото профиля Gorilla Furkan | Integrated 🦍⚡️
Gorilla Furkan | Integrated 🦍⚡️1 год назад

@rushimanche GMOVE

Фото профиля TOP SIGNAL🔝
TOP SIGNAL🔝1 год назад

"OpenLedger's LoRA fine-tuning demo is a glimpse into how blockchain can decentralize AI training. Data integrity meets scalability—AI's future is trustless."

Фото профиля dekompoza_Ng🪀⛽️
dekompoza_Ng🪀⛽️1 год назад

We know it’s all about #Openledger

Фото профиля Chopin Frédéric
Chopin Frédéric1 год назад

This whole video doesn't show a single line of generated move code. Just a scam ...

Фото профиля Novastro | RWA L2
Novastro | RWA L21 год назад

AI on MOVE

Фото профиля KRMC | SUPRA
KRMC | SUPRA1 год назад

GN #openledger #opnup.

Фото профиля Tameryus | INTEGRATED 🦍 ⚡
Tameryus | INTEGRATED 🦍 ⚡1 год назад

AI MOVE

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Many people are flat wrong about DeepSeek. You might think everyone freaked out about DeepSeek because the model is really good—which it is—or because it was from China, which is also true. But there's a more subtle reason: DeepSeek showed they could achieve those results using reinforcement learning instead of supervised fine-tuning. In other words, they didn't need an expensive phase where a bunch of people tuned the model by answering questions. They were able to do all of this faster and cheaper using reinforcement fine-tuning. This is a huge deal! I recorded the attached video with the following goals in mind: 1. Explain how reinforcement fine-tuning works 2. Show you how you can fine-tune your own models 3. Walk you through a complete code example

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