LLama 2: Andrej Karpathy, GPT-4 Mixture of Experts - AI Paper Explained скачать в хорошем качестве

LLama 2: Andrej Karpathy, GPT-4 Mixture of Experts - AI Paper Explained

Watch as we take the groundbreaking Baby Llama 2 model from PyTorch and unleash its potential with a one-of-a-kind 500-line file in pure C for seamless inference, and the best part? No dependencies required. Pretrained on TinyStories, this baby llama is no ordinary model! Witness its incredible story-sampling prowess, churning out tales at a staggering 18 tokens per second on the MacBook Air M1 CPU in fp32. Sparse Mixture-of-Experts (MoE) is a neural architecture design that can be utilized to add learnable parameters to Large Language Models (LLMs) without increasing inference cost. Instruction tuning is a technique for training LLMs to follow instructions. We advocate combining these two approaches, as we find that MoE models benefit more from instruction tuning than dense models. CM3Leon (pronounced “Chameleon”), a retrieval-augmented, tokenbased, decoder-only multi-modal language model capable of generating and infilling both text and images. CM3Leon uses the CM3 multi-modal architecture but additionally shows the extreme benefits of scaling up and tuning on more diverse instruction-style data. Using only a single input image, HyperDreamBooth is able to personalize a text-to-image diffusion model 25x faster than DreamBooth. Andrej Karpathy LLama 2 on C - Github: https://github.com/karpathy/llama2.c Tweet:   / 1683143097604243456   Mixture-of-Experts Meets Instruction Tuning - Paper: https://arxiv.org/abs/2305.14705 Latent Space George Hotz:    • Ep 18: Petaflops to the People — with Geor...   CM3Leon / Scaling Autoregressive Multi-Modal Models - Paper: https://ai.meta.com/research/publicat... Blog: https://ai.meta.com/blog/generative-a... HyperDreamBooth: HyperNetworks - Paper: https://arxiv.org/abs/2307.06949 Blog: https://hyperdreambooth.github.io/ https://www.buymeacoffee.com/harrym https://substack.com/@harrymap