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Excited to share a glimpse of what’s possible with specialized models on OpenLedger🐙 In this video, you’ll see a chat agent in action—think of it as the Perplexity of crypto. Powered by tool calling, this specialized model showcases how OpenLedger enables domain-specific intelligence for AI-driven apps. Vision of these...

87,959 Aufrufe • vor 1 Jahr •via X (Twitter)

11 Kommentare

Profilbild von KRMC | SUPRA
KRMC | SUPRAvor 1 Jahr

Güzel anlatım. Teşekkürler. #openledger #opnup

Profilbild von Lab4crypto
Lab4cryptovor 1 Jahr

🚀 Don't gamble with your portfolio! Use our advanced hybrid quant risk tool using on/off-chain data and make informed decisions. 📈 Acess to 1000+ charts for your crypto journey. 📚Join our Premium Telegram for daily alerts. 📊+21 projects supported. 🏗️ Beginners and experts.

Profilbild von Ozzi.sol (Ø,G) (✸,✸)
Ozzi.sol (Ø,G) (✸,✸)vor 1 Jahr

IS THE @OpenledgerHQ DEVELOPING THIS, DUDE?

Profilbild von S a n t o s 𓊈𒆜🐙𒆜𓊉
S a n t o s 𓊈𒆜🐙𒆜𓊉vor 1 Jahr

cooking ❤️‍🔥 #Openledger #Opnup

Profilbild von UV
UVvor 1 Jahr

Something Deep?! you’re Digging Guys. 👌

Profilbild von Noah (Ø,G)
Noah (Ø,G)vor 1 Jahr

Wow! Already looking great, looking forward to the final product #Opnup

Profilbild von ꧁IP꧂ crypto king CLONE (✸,✸) (Ø,G)
꧁IP꧂ crypto king CLONE (✸,✸) (Ø,G)vor 1 Jahr

Great project

Profilbild von Lilremedy
Lilremedyvor 1 Jahr

Something is cooking @OpenledgerHQ , so sorry for faders 😂

Profilbild von DigitalNomad 𓊈𒆜🐙𒆜𓊉꧁IP꧂
DigitalNomad 𓊈𒆜🐙𒆜𓊉꧁IP꧂vor 1 Jahr

Revolutionize everything AI! #Opnup

Profilbild von Mazher Shahzad (web3cryptoworld)
Mazher Shahzad (web3cryptoworld)vor 1 Jahr

to the moon #Openledger #Opnup

Profilbild von Vicky Sharma (✸,✸) CLONE ⛺ Kaisar
Vicky Sharma (✸,✸) CLONE ⛺ Kaisarvor 1 Jahr

cooking ❤️‍🔥 #Openledger #Opnup

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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 Aufrufe • vor 2 Jahren