Ready to fine-tune the hottest new open-source LLM—#Mixtral 8x7B—with best practice #optimizations in just a few lines of code? We got you covered! Read our tutorial to see how easy & efficient it is to #finetune Mixtral w/ open-source @ludwig_ai https://
pbase.ai/4audc8U
OPEN SOURCE
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Fine-tuning Mixtral 8x7B with Ludwig AI: Easy Optimization
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Advanced RAG Applications with LangChain, Llama Index, Deep Memory
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We go beyond basic RAG applications, equipping you with the skills to create more complex, reliable products with tools like @langchain
, @llama_index (with insights from @jerryjliu0
), and Deep Memory. Whether you're a beginner or professional, join us to elevate your AI skills! -
Open vs. Closed Source LLMs Webinar Starting Now
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Starting now, @bindureddy will kick off this webinar by chatting about open vs. closed source LLMs
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Open-Source AI Agent Automates Google Calendar Management
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Open-Source Google Calendar Assistant Managing one's calendar can be a repetitive task – perfect for automation with an AI agent @jackgordley
's recent open source project tackles exactly that! Blog: https://
gordles.io/posts/calvin
Code: https://
github.com/jgordley/Googl
eCalendarAssistant
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LCM and Turbo Models Guide for Stable Diffusion
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A new section in our stable diffusion guide – a one page explainer on LCM, LCM Loras and Turbo models: https://
replicate.com/guides/stable-
diffusion/turbo-and-latent-consistency
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OpenCV Universe Holiday Surprise Coming Soon
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🎁 Sneak Peek Alert! @OpenCVUniverse is about to drop a holiday surprise that will redefine your tech journey. Keep your 👀 peeled! #holidayseason #ComputerVision #AI pic.twitter.com/EIfLzKa1M6
— Satya Mallick (@LearnOpenCV) 19 décembre 2023Sneak Peek Alert! @OpenCVUniverse is about to drop a holiday surprise that will redefine your tech journey. Keep your peeled! #holidayseason #ComputerVision #AI
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Small Language Models: Accessible Training and Deployment Solutions
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Training large language models is a very technically demanding and resource intensive task. Many such models also require lots of specialized compute to use. Fortunately, we have recently been blessed by public releases of several "small" LLMs 1/4
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PyTorch Uses Own Tensor Engine, Not NumPy
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Actually, PyTorch does not build on NumPy.
It uses its own tensor engine with GPU support, compilation, etc.
The only dependencies on NumPy is to provide some interoperability between NumPy arrays and Torch tensors. -
Jerry Liu on AI Future: LlamaIndex, RAG, and LLM Solutions
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@jerryjliu0 on the Future of AI: @llama_index, LLMs, RAG, Prompting and more!
— Louis-François Bouchard 🎥🤖 (@Whats_AI) 19 décembre 2023
In this 25th episode, Jerry, co-founder and CEO of LlamaIndex shares valuable insights for anyone implementing LLM solutions. I decided to focus on Retrieval Augmented Generation (RAG) since it is the… pic.twitter.com/oIDkeSUsJ7@jerryjliu0 on the Future of AI: @llama_index
, LLMs, RAG, Prompting and more! In this 25th episode, Jerry, co-founder and CEO of LlamaIndex shares valuable insights for anyone implementing LLM solutions. I decided to focus on Retrieval Augmented Generation (RAG) since it is the -
Google Releases Seven LangChain Notebooks for Gemini Integration
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LangChain x Google The official Google `generative-ai` repo has a ton of resources for getting started with Gemini This includes SEVEN different notebooks for using LangChain to orchestrate a Gemini-powered LLM app Dive into all the goodness: https://
github.com/GoogleCloudPla
tform/generative-ai/tree/main/language/orchestration/langchain
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