How can you use state-of-the-art generative vision models? comfyui from Comfy Org is a powerful and modular diffusion model GUI, api and backend with a graph/nodes interface. It's one of the leading tools in image-based generative AI. https://lnkd.in/gE_yNP4J Now you can get help using comfyui by chatting with the repo on Storia Sage. https://lnkd.in/eewqNqbz
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Today, I came across an impressive presentation by Scott Penberthy The discussion highlighted how workflows serve as the modern micro services for AI, contrasting the traditional one-size-fits-all monolith model. What are your thoughts on this insightful perspective?
GitHub - comfyanonymous/ComfyUI: The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.
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New Medium Article: "How to Distribute HuggingFace Models Across Multiple GPUs." I’ve just published the latest piece in my series on optimizing deep learning workflows. This time, I’m covering how to efficiently distribute Hugging Face models over multiple GPUs to boost your training speed and handle larger models. Catch the full guide here: https://lnkd.in/gsZ4e5uU Follow me on Medium for more such articles. Happy learning! #MachineLearning #DeepLearning #HuggingFace #PyTorch #MultiGPU #AI #Medium
How to Distribute HuggingFace Models Across Multiple GPUs.
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Hello, I’m sharing a post that explains how to set up a Kubernetes cluster with GPU resources. The post concludes with the deployment of Ollama, an application that exposes generative AI models, such as LLMs, via a REST API. Feel free to provide feedback by replying to this message or directly on my blog. ➡️ https://lnkd.in/enikbWW9 (I attest that the blog post and this LinkedIn message were written by a real human🤖)
A step-by-step pratical guide for deploying NVIDIA GPUs on Kubernetes
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🚀 Thrilled to share that my first Stable Diffusion tutorial is now live! In this tutorial, I walk through the process of deploying your own Stable Diffusion AI-powered image generator. It’s perfect for those curious about diving into AI, or for anyone looking to sharpen their tech skills. This guide also highlights the upcoming GPU Droplet from DigitalOcean, helping you harness its power to generate artistic images with various models. It’s just the start, and there’s more coming! I’m excited to contribute to the growing AI community, and I’d love to hear your thoughts! Feel free to reach out with any feedback💡 #AI #StableDiffusion #Tutorial #GenerativeAI #GPUDroplet #DigitalOcean
Stable Diffusion Made Easy: Get Started on DigitalOcean GPU Droplets
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Top 5 Machine Learning APIs Practitioners Should Know Learn about machine learning APIs for datasets, models, web applications, free GPUs, and text, audio, and image generation.
Top 5 Machine Learning APIs Practitioners Should Know - KDnuggets
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Top 5 Machine Learning APIs Practitioners Should Know Learn about machine learning APIs for datasets, models, web applications, free GPUs, and text, audio, and image generation https://lnkd.in/eM_tYSHy
Top 5 Machine Learning APIs Practitioners Should Know - KDnuggets
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Top 5 Machine Learning APIs Practitioners Should Know https://lnkd.in/dMvcj6Ub. Learn about machine learning APIs for datasets, models, web applications, free GPUs, and text, audio, and image generation.
Top 5 Machine Learning APIs Practitioners Should Know - KDnuggets
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Those of you who attended my sessions during the 'Build with AI' series of events already know I’ve been exploring some of the different use cases for RAG (Retrieval Augmented Generation) to empower developers by providing them with the tools and access to knowledge that would push them forward in their learning and development processes 🚀. A few weeks ago my latest article on my series of AI publications was released: “Your RAG-powered AI app in 50 lines of code!”. 📖 In this article, I show you how to make an LLM give you insights into a company’s products by leveraging their public documentation website’s repository, everything within a few lines of code thanks to LlamaIndex, Ollama, and Qdrant. I briefly talk about the main concepts you need to keep in mind – without going into too much detail – because as I’ve said in the past, you should “leave the deep complex stuff for later” and focus on creating something that works first. I’d love to hear your feedback and see what you build using these technologies – that indeed run faster on specialized hardware, such as NVIDIA’s H100 or L4 GPUs, but can also run on consumer-grade CPU & GPU hardware (yes, even your Intel Corporation GPUs!). https://lnkd.in/gFvRTdFP #AI #DevRel #DeveloperAdvocacy #openSource #rag #llm
Your RAG powered AI app in 50 lines of code | Scaleway
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Just discovered BitNet from Microsoft, which is making waves in the AI landscape! This inference framework is capable of managing an astonishing 100 billion parameters, designed to operate at supercomputer levels but can run on standard CPU setups!! It integrates 1-bit LLMs, making it an impressive tool for efficient image generation and other AI tasks. This advancement could significantly enhance accessibility for developers interested in generative AI without the need for heavy computational resources. For more detailed insights, check out the BitNet GitHub page. GitHub: https://lnkd.in/gRsHuhqe #BitNet #Microsoft #AI #MachineLearning #ImageGeneration #GenerativeAI #1BitLLMs #Innovation #TechTrends #ArtificialIntelligence #DeepLearning #DataScience
GitHub - microsoft/BitNet: Official inference framework for 1-bit LLMs
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🚨 Breakthrough Announcement: ThirdAI Shatters AI Benchmarks🚨 Hot off the press! Thirdai's latest release just upped the ante on efficient document indexing. Compared on the colossal MSMarco BEIR Benchmark — the largest of its kind — we've not only met but exceeded state-of-the-art (SoTA) accuracy, and we've done it in record time. Imagine deploying a system with unparalleled precision in less time than it takes to finish reading this post. 🔍 Benchmarking the Future of Search We put our system to the test against the biggest names in the industry, and here are the groundbreaking results: - Elastic Search: Precision@1: 0.65 - Google T5-Base: Precision@1: 0.56 - OpenAI Ada: Precision@1: 0.81 - ThirdAI (Before Finetuning): Precision@1: 0.79 - ThirdAI (After Finetuning): Precision@1: 0.814 💡 ThirdAI's Unmatched Efficiency The efficiency of ThirdAI is unmatched, revolutionizing the landscape of AI-driven search systems. Not only does ThirdAI provide results comparable to the highest standards set by industry, but it also does so with a fraction of the resources and time. 🌐 From Benchmarks to Breakthroughs ThirdAI's latest achievement isn't just about numbers; it's a testament to our commitment to pushing the boundaries of what AI can achieve. By harnessing the power of finetuning, we've demonstrated that our system is not just another search or RAG engine — it's a continuously evolving AI system, designed to grow smarter with every query. ✨ Join the Revolution This is just the beginning. ThirdAI is on a mission to democratize access to powerful, efficient, and intelligent search systems. Whether you're a researcher, developer, or business leader, there's never been a better time to explore how ThirdAI can transform your work and insights. 🔗 Try it for yourself Want to check it out for yourself? Read the entire blog and try out the attached notebook to learn more about our groundbreaking technology and how you can leverage it to unlock new horizons of knowledge and innovation. #ThirdAI #AIRevolution #MachineLearning #AIInnovation #DataScience #BreakthroughAI
STA Q&A over MSMarco text (~9M chunks) in 4 minutes on Laptop
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