Alibaba/Qwen

最新のAIニュース、モデル、リリース元 Alibaba/Qwen. ['CodeQwen1.5', 'Cotype Light 3', 'Cotype Pro 3', 'Fun-Realtime-TTS', 'Hanguang', 'Hanguang 800', 'HappyOyster 1.0', 'ICN Switch 1.0', 'not specified', 'Panjiu', 'Qianwen', 'Qoder Security', 'QVQ-72B-Preview', 'QVQ-Max', 'Qwen', 'Qwen 2', 'Qwen2.5', 'Qwen2.5-14B-Instruct-1M', 'Qwen2.5-32B', 'Qwen-2.5 72B', 'Qwen2.5-7B', 'Qwen2.5-7B-Instruct-1M', 'Qwen2.5-Coder', 'Qwen2.5-Coder-0.5B', 'Qwen2.5-Coder-0.5B-Instruct', 'Qwen2.5-Coder-14B', 'Qwen2.5-Coder-1.5B', 'Qwen2.5-Coder-1.5B-Instruct', 'Qwen2.5-Coder-32B', 'Qwen2.5-Coder-32B-Instruct', 'Qwen2.5-Coder-3B', 'Qwen2.5-Coder-3B-Instruct', 'Qwen2.5-Coder-7B', 'Qwen2.5-Coder-7B-Instruct', 'Qwen2.5-Coder-Instruct', 'Qwen2.5-Math-1.5B', 'Qwen2.5-Math-1.5B-Instruct', 'Qwen2.5-Math-72B', 'Qwen2.5-Math-72B-Instruct', 'Qwen2.5-Math-7B']

研究 🇺🇸

New DeepSeek-V3 Technical Report: How Hardware-Software Codesign Enables Low-Cost Training of Large Models

A new 14-page technical report from the DeepSeek-V3 team, co-authored by DeepSeek CEO Wenfeng Liang, has been released. The document analyzes the scaling challenges of large language models and the role of hardware infrastructure, proposing solutions based on joint design of models and hardware for cost-effective training and inference.

DeepSeekDeepSeek NVIDIANVIDIA Alibaba/QwenAlibaba/Qwen MetaMeta
Synced27.07 · 18:04
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