DeepSeek-V3
DeepSeek-V3 is a powerful Mixture-of-Experts (MoE) language model with 671 billion total parameters and 37 billion activated parameters per token. It achieves efficient inference and cost-effective training through innovative load balancing strategies and multi-token prediction training objectives. The model is pre-trained on 14.8 trillion diverse and high-quality tokens, and it outperforms other open-source models in various benchmarks.
Részletes Bevezetés
DeepSeek-V3 is a cutting-edge AI model that has achieved a notable breakthrough in inference speed, making it one of the fastest models available. It excels in multiple benchmarks, including language understanding, code generation, and mathematical problem-solving. DeepSeek's architecture, which includes Mixture of Experts (MoE), allows it to activate a subset of parameters efficiently, enhancing its performance while maintaining a large total parameter count. This model is designed to provide high accuracy and efficiency, making it suitable for a wide range of applications.
TöbbMesterséges intelligencia
Remento: Capture Family Stories and Preserve Memories
Remento transforms spoken memories into personalized keepsake books, making it easy to preserve and share family stories. With our Speech-To-Story™ technology, you can turn your loved ones' recordings into beautifully written stories that include their voice. Perfect for capturing life's moments and creating an unforgettable gift.
ICASSP2022-Depression: Automatic Depression Detection
This repository provides code and data for automatic depression detection using a GRU/BiLSTM-based model. It includes an emotional audio-textual corpus designed to support the diagnosis of psychological distress conditions such as anxiety, depression, and post-traumatic stress disorder.
STORM
STORM is a research project from the Stanford OVAL lab. It is designed to help users create documents by searching for information and integrating it into text. The tool is still under development and may generate offensive content or make mistakes.