
Large language models (LLMs) are revolutionizing language processing by enabling tasks like text generation, translation, and more. Foundational LLMs with high sparsity are enhancing AI capabilities in chat, code generation, and summarization. Nvidia introduces NV-Embed with improved techniques for training LLMs as generalist embedding models.
A New Approach to Language Model Scaling: Predicting Future Capabilities with Observational Scaling Laws #AI #AItechnology #artificialintelligence #LanguageModelScaling #llm #machinelearning https://t.co/UVEMN9jxQA https://t.co/nvsvy91NfB
NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models Nvidia introduces an embedding model with architectural improvements like latent attention pooling and a 2-stage contrastive instruction-tuning. 📝https://t.co/1BnwvIDe3D 👨🏽💻https://t.co/QNZjZB0Pt4 https://t.co/cZ85I7OQHI
This is probably the first highly sparse, foundational LLMs with full recovery on several fine-tuning tasks, including chat, code generation, summarization, and more. Paper - "Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment" The… https://t.co/srIAxfON9r


