[AI Fusion] LLAMA 3.1 70b GPU Requirements (FP32, FP16, INT8 and INT4)

🎯 Загружено автоматически через бота: 🚫 Оригинал видео: 📺 Данное видео является собственностью канала AI Fusion. Оно представлено в нашем сообществе исключительно в информационных, научных, образовательных или культурных целях. Наше сообщество не утверждает никаких прав на данное видео. Пожалуйста, поддержите автора, посетив его оригинальный канал: @AIFusion-official. ✉️ Если у вас есть претензии к авторским правам на данное видео, пожалуйста, свяжитесь с нами по почте support@, и мы немедленно удалим его. 📃 Оригинальное описание: This Tool allows you to choose an LLM and see which GPUs could run it... : Welcome to this deep dive into the world of Llama 3.1, the latest and most advanced large language model from Meta. If you’ve been amazed by Llama 3, you’re going to love what Llama 3.1 70B brings to the table. With 70 billion parameters, this model has set new benchmarks in performance, outshining its predecessor and raising the bar for large language models. In this video, we’ll break down the GPU requirements needed to run Llama 3.1 70B efficiently, focusing on different quantization methods such as FP32, FP16, INT8, and INT4. Each method offers a unique balance between performance and memory usage, and we’ll guide you through which GPUs are best suited for each scenario—whether you’re running inference, full Adam training, or low-rank fine-tuning. To make your life easier, I’ve developed a free tool that allows you to select any large language model and instantly see which GPUs can run it at different quantization levels. You’ll find the link to this tool in the description below. If you’re serious about optimizing your AI workloads and want to stay ahead of the curve, make sure to watch until the end. Don’t forget to like, subscribe, and hit the notification bell to stay updated with all things AI! Tags: #Llama3 #MetaAI #GPUrequirements #QuantizationMethods #AIModels #LargeLanguageModels #FP32 #FP16 #INT8 #INT4 #AITraining #AIInference #AITools #llmgpu #llm #gpu #AIOptimization #ArtificialIntelligence