4/ Meta’s open-source approach enables:
– Accessibility: Developers worldwide can customize and build on Llama 4.
– Democratization: Contrasts with closed ecosystems like OpenAI and Google.
– Commercial Impact: AI-driven advertising and content creation take center stage.
OPEN SOURCE
-
Meta’s Open-Source Llama 4: Accessibility, Democratization, Commercial Impact
By
–
-
Llama 4 Trained on 100,000 Nvidia H100 GPUs Infrastructure
By
–
3/ Powered by Cutting-Edge Infrastructure Trained on 100,000+ Nvidia H100 GPUs, Llama 4 demonstrates Meta’s commitment to pushing the limits of AI performance and scalability.
-
Meta Announces Llama 4 Open-Source AI Model Coming 2025
By
–
1/ 🚀 Meta Announces Llama 4
— Giuliano Liguori (@ingliguori) 7 décembre 2024
Mark Zuckerberg has unveiled Llama 4, the next-gen open-source AI language model, coming in early 2025. Here’s why this is a game-changer for AI innovation and accessibility. 🧵👇 pic.twitter.com/VgY1K2mSsG1/ Meta Announces Llama 4
Mark Zuckerberg has unveiled Llama 4, the next-gen open-source AI language model, coming in early 2025. Here’s why this is a game-changer for AI innovation and accessibility. -
Llama 3.3 70B Matches 405B Quality with Superior Speed
By
–
Llama 3.3 70B quality scores are surprisingly close to the larger 405B model. That's a huge win for developers – no more trading off speed & high-quality in text-based applications Read more here https://
hubs.la/Q02-QgDq0 or skip straight to building at https://
hubs.la/Q02-QcJ80. -
Llama 3.3 70B Matches 405B Quality with Superior Speed
By
–
Llama 3.3 70B quality scores are surprisingly close to the larger 405B model. That's a huge win for developers – no more trading off speed & high-quality in text-based applications Read more here https://
groq.link/llama3refresh or skip straight to building at http://
console.groq.com. -
Loading Knowledge Base Documents in LlamaIndex for RAG
By
–
& : Loading the knowledge base A knowledge base is a collection of relevant and up-to-date information that serves as a foundation for RAG. In our case it's the docs stored in a directory. Here's how you can load it as document objects in LlamaIndex:
-
Building a Local RAG System with LlamaIndex and Ollama
By
–
Before we begin, take a look at what we're about to create!
— Akshay 🚀 (@akshay_pachaar) 7 décembre 2024
Here's what you'll learn:
– @Llama_Index for orchestration
– @qdrant_engine to self-host a vector DB
– @Ollama for locally serving Llama-3.3
– @LightningAI for development & hosting
Let's go! 🚀 pic.twitter.com/qIKJjv0mxJBefore we begin, take a look at what we're about to create! Here's what you'll learn: – @Llama_Index for orchestration
– @qdrant_engine to self-host a vector DB
– @Ollama for locally serving Llama-3.3
– @LightningAI for development & hosting Let's go! -
Building a Local RAG Application with MetaAI’s Llama-3.3
By
–
Let's build a RAG app using MetaAI's Llama-3.3 (100% local):
-
Major VLM Revolution: Open-Source Models from Google, OpenGVLabs, Qwen, Microsoft
By
–
VLMs are going through quite an open revolution AND on-device friendly sizes: > Google DeepMind w/ PaliGemma2 – 3B, 10B & 28B > OpenGVLabs w/ InternVL 2.5 – 1B, 2B, 4B, 8B, 26B, 38B & 78B > Qwen w/ Qwen 2 VL – 2B, 7B & 72B > Microsoft w/ FlorenceVL – 3B & 8B (Links below)
-
AgentLab: Open Source Framework for Web Agents
By
–
[#Article] AgentLab, an open source framework for the development and evaluation of Web agents https://actuia.com/actualite/agentlab-un-framework-open-source-pour-le-developpement-et-levaluation-des-agents-web/
…
#AI #artificialintelligence