Unverified60% confidenceFactTime unknown
GPT-4、LLaMA、Qwen等主流生成式大模型采用Decoder-only架构;BERT、RoBERTa采用Encoder-only架构;T5、BART采用Encoder-Decoder架构
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
Valid until: 9/30/2026
Sources
Transformer架构核心原理:自注意力机制与工程优化深度解析
bilibiliAI大模型_全能版
Related Claims
VerifiedBERT 采用编码器架构,GPT 系列采用解码器架构,T5 和 BART 采用编码器-解码器架构79% similarPartially VerifiedGPT系列采用了仅解码器(Decoder-only)架构79% similarVerifiedGPT-4和Mixtral等主流大模型也采用了MoE架构74% similarUnverifiedLlama 3.1(Meta)、Mistral 7B/8x7B、Qwen2.5-Coder(阿里云)等开源模型在代码和配置生成任务上达到接近 GPT-4 的实用水平73% similarUnverified成熟的开发者应同时掌握国内的DeepSeek、Qwen以及国外的OpenAI GPT-4o、o3、Claude 3.5/3.7/4.0等多个模型72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/59793API
curl https://kongchang.com/api/v1/knowledge/claims/59793MCP
get_claim(id=59793)