点击上方“Deephub Imba”,关注公众号,好文章不错过 !这篇文章从头实现 LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architectures。需要说明的是，这里写的是一个简洁的最小化训练脚本，目标是了解 JEPA 的本质：对同一文本创建两个视图，预测被遮蔽片段的嵌入，用表示对齐损失来训练。本文的目标是 ...
Tokens are the fundamental units that LLMs process. Instead of working with raw text (characters or whole words), LLMs convert input text into a sequence of numeric IDs called tokens using a ...
What makes a large language model like Claude, Gemini or ChatGPT capable of producing text that feels so human? It’s a question that fascinates many but remains shrouded in technical complexity. Below ...
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