Загрузка видео...

Не удалось загрузить видео

На главную

Our Hyperbolic agent can now perform fine-tuning tasks! This is a step forward for our self-evolving agent vision. Kudos to Zile from Blockchain Capital! This is how it works: 1. sync files to remote machine 2. install relevant dependencies 3. run an initial Unsloth AI fine-tune task 4. do...

20,693 просмотров • 1 год назад •via X (Twitter)

Комментарии: 11

Фото профиля Jasper
Jasper1 год назад

Check out the PR:

Фото профиля Jasper
Jasper1 год назад

I met @zile_cao at @coinbase @CoinbaseDev agent hackathon two weeks ago. While his team didn't finish the self-evolving bounty at that time, we were still amazed by their understanding of our agent framework and the progress. We decided to give them the bounty and it motivated him to continue building on our agent framework. Hackathon is the best place to build out the developer community. We have met so many talented builders and all of them are building toward AI's open future 💜

Фото профиля Togoda AI Search Engine
Togoda AI Search Engine1 год назад

Togoda is Google on Steroids with AI summaries . 🚀 The only thematic AI search engine.👀 It's 100% private with third party proxy. 🧨 Try it today & experience the difference! 👉Follow us @togoda_com 👈 🚀Help us grow & share this post!🚀

Фото профиля Hyperbolic
Hyperbolic1 год назад

@zile_cao @blockchaincap @UnslothAI Accelerate!

Фото профиля Eazydoe.apt (🏴‍☠️,🌐)
Eazydoe.apt (🏴‍☠️,🌐)1 год назад

@hyperbolic_labs @zile_cao @blockchaincap @UnslothAI Sounds like progress, but while you're taking steps, the rest are already winning. If you want to outpace, look at BlockProtocol's Web3 AI-driven marketing tool—already a game-changer.

Фото профиля 🐧 lalo adrian morales 𝕏
🐧 lalo adrian morales 𝕏1 год назад

@hyperbolic_labs @zile_cao @blockchaincap @UnslothAI that was one of the best tutorials ive ever seen.. and i watch a crap load. great job man

Фото профиля Crypto Gyan
Crypto Gyan1 год назад

@hyperbolic_labs @zile_cao @blockchaincap @UnslothAI Fine tuning is future, tailoring models to specific tasks for faster, smarter, and more efficient performance.

Фото профиля 𝙅𝙖𝙮𝙈☂️
𝙅𝙖𝙮𝙈☂️1 год назад

@hyperbolic_labs @zile_cao @blockchaincap @UnslothAI Incredible leap for AI! #Hyperbolic’s crushing it with this fine-tuning upgrade and GPU Marketplace expansion huge props all around

Фото профиля Ayush Mudgal
Ayush Mudgal1 год назад

@hyperbolic_labs @zile_cao @blockchaincap @UnslothAI How do you curate the dataset for this fine tune run? Also amazing to see the usage of @UnslothAI!

Фото профиля Jasper
Jasper1 год назад

@zile_cao @blockchaincap @UnslothAI If you're building some cool apps or agents on Hyperbolic, share the demos with me and I'm happy to share them publicly!

Фото профиля bigray0x.eth 🌱
bigray0x.eth 🌱1 год назад

@hyperbolic_labs @zile_cao @blockchaincap @UnslothAI Keep shipping sir 🫡

Похожие видео

Small Language Models (SML) are the future of AI. "Small" (SML) instead of "Large" (LLM). These small models are highly specialized models with superhuman abilities on specific tasks. Here are two techniques to build these models: • Spectrum • Model Merging I give you a short introduction in the attached video, but here is a quick summary: Spectrum helps us identify the most relevant layers to solve one specific task. We can ignore everything else and focus on fine-tuning these layers. Using Spectrum, we can fine-tune models in a heartbeat. Model Merging combines multiple models into a unique, much better model than any of the individual input models. You can also combine models specialized in different tasks and get a model with multiple abilities. This is the state of the art of productizing models. It's what Arcee.ai's platform does behind the scenes. Arcee collaborated with me on this post and is sponsoring it. There are three main steps to produce a model for your particular use case: 1. You create a dataset by uploading your data. 2. You train a model. At this step, Arcee uses Spectrum and Model Merging to produce a highly specialized model for your task. 3. You can deploy that model to any environment you want. Three important notes: • Training process is 2x faster and 2x cheaper than regular fine-tuning. • Resultant models are smaller and have higher accuracy. • They create these specialized models from open-source models. Check this site so you can fully appreciate how this works: If you want to fine-tune an open-source model, consider Arcee's platform. This is the state of the art.

Santiago

164,162 просмотров • 1 год назад