Paper : Github: [ Ссылка ]
This approach allows us to extend the effective context window of a 4k LLaMA2-7B model to handle up to 128k tokens. Moreover, the paper achieves state-of-the-art results that match or even surpass the performance of a LLaMA2-7B-32k model with full context on long context benchmarks, while using 30 times fewer tokens."
Paper - "LLoCO: Learning Long Contexts Offline"
🐦 TWITTER: [ Ссылка ]
Checkout the MASSIVELY UPGRADED 2nd Edition of my Book (with 1300+ pages of Dense Python Knowledge) 🐍🔥
Covering 350+ Python 🐍 Core concepts ( 1300+ pages ) 🚀
🟠 Book Link - [ Ссылка ]
-----------------
Hi, I am a Machine Learning Engineer | Kaggle Master. Connect with me on 🐦 TWITTER: [ Ссылка ] - for daily in-depth coverage of Large Language Model bits
----------------
You can find me here:
**********************************************
🐦 TWITTER: [ Ссылка ]
👨🏻💼 LINKEDIN: [ Ссылка ]
👨🔧 Kaggle: [ Ссылка ]
👨💻 GITHUB: [ Ссылка ]
🧑🦰 Facebook Page: [ Ссылка ]
📸 Instagram: [ Ссылка ]
**********************************************
Other Playlist you might like 👇
🟠 MachineLearning & DeepLearning Concepts & interview Question Playlist - [ Ссылка ]
🟠 ComputerVision / DeepLearning Algorithms Implementation Playlist - [ Ссылка ]
🟠 DataScience | MachineLearning Projects Implementation Playlist - [ Ссылка ]
🟠 Natural Language Processing Playlist : [ Ссылка ]
----------------------
#LLM #Largelanguagemodels #Llama2 #LLMfinetuning #opensource #NLP #ArtificialIntelligence #datascience #textprocessing #deeplearning #deeplearningai #100daysofmlcode #neuralnetworks #datascience #generativeai #generativemodels #OpenAI #GPT #GPT3 #GPT4 #chatgpt #genai
![](https://i.ytimg.com/vi/G_x0xHkbFnY/maxresdefault.jpg)