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36,486 görüntüleme • 1 yıl önce •via X (Twitter)

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Monique Santificer profil fotoğrafı
Monique Santificer1 yıl önce

I remember this making my dad laugh so much he hurt himself and couldn't breathe right for a week

Solar Heavy profil fotoğrafı
Solar Heavy1 yıl önce

We're Flying out now

Hex’d Uni profil fotoğrafı
Hex’d Uni1 yıl önce

THATS WHERE THIS IS FROM?

Vinesauce Clips Bot profil fotoğrafı
Vinesauce Clips Bot1 yıl önce

Title: JAMBA AYUSS Game: Special Events Clipped by: OfficialJlipper Clipped on: April 14, 2025

Highretrogamelord☯ profil fotoğrafı
Highretrogamelord☯1 yıl önce

We had a lot of Jamba commercials in the 2000s here in Germany on music channels like MTV and Viva. They were so god damn annoying!

Borreload Dragon profil fotoğrafı
Borreload Dragon1 yıl önce

Sensual, (un movimiento sensual) un movimiento muy sexy (sexy)...

Salsa profil fotoğrafı
Salsa1 yıl önce

i feel like i remember seeing this hippo as a kid

bruno profil fotoğrafı
bruno1 yıl önce

this is hot

GUARD FISH 😳 profil fotoğrafı
GUARD FISH 😳1 yıl önce

Ig we found someone that’s somehow worse than this guy | V

SneakGoblin7 🇵🇸🌎 profil fotoğrafı
SneakGoblin7 🇵🇸🌎1 yıl önce

Joel voice spotted

JP profil fotoğrafı
JP1 yıl önce

Moo deng fell on hard times 😔

Viscount01 profil fotoğrafı
Viscount011 yıl önce

I'm thankful for my weird nightmares that don't include purple dancing hippos.

El pvto de Rizus profil fotoğrafı
El pvto de Rizus1 yıl önce

Tra tra tra tra

Benzer Videolar

New short course: Build Long-Context AI Apps with Jamba. Learn about state space models (SSMs), which have emerged as an alternative to transformers! Specifically, Jamba is a hybrid transformer-Mamba architecture that combines strengths of the transformer with ideas from SSMs. This course is built with AI21 Labs and taught by Chen Wang and Chen Almagor. The transformer architecture is computationally expensive when handling very long input contexts. But there's an alternative called Mamba, a selective state space model that can process very long contexts with a much lower computational cost. However, researchers found that the pure Mamba architecture underperforms in understanding the context, and gives lower-quality responses. To overcome this, AI21 developed the Jamba model, which combines Mamba's computational efficiency with the transformer's attention mechanism to help with the output quality. In this course, you’ll learn about how state space models, and Jamba, work. You’ll also learn how to prompt Jamba, use it to process long documents, and build long-context RAG apps. - Learn how Jamba combines transformer and state space model architectures to achieve high performance and quality - Use the AI21 SDK, with an example of prompting over a large 200k-token annual financial report of Nvidia - Use Jamba for tool-calling, with hands-on examples from calling simple arithmetic calculations to a function that returns quarterly company financial reports. - Learn how training for long context is done, and the metrics used for its evaluation - Create a RAG app using the AI21 Conversational RAG tool and build your own RAG pipeline that uses Jamba and LangChain. By the end of this course, you'll learn how to build applications that can handle context as long as an entire book. Please sign up here:

Andrew Ng

77,792 görüntüleme • 1 yıl önce