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| data_analysis:statistics_and_machine_learning [2024/07/05 05:52] – [유사도 Encoder] prgram | data_analysis:statistics_and_machine_learning [2025/07/07 14:12] (current) – external edit 127.0.0.1 | ||
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| [[data_analysis: | [[data_analysis: | ||
| - 디코더만 사용 | - 디코더만 사용 | ||
| + | - Large model이면 디코더만 있어도 decoder-only models can internally encode necessary context from prior tokens, reducing the need for an explicit encoder. | ||
| + | - Decoder-only models still leverage self-attention (though in a causal form), allowing them to capture dependencies efficiently. | ||
| + | - Many tasks that traditionally required encoder-decoder architectures can now be handled end-to-end with a sufficiently large decoder-only model. | ||
| + | - With enough training data, a decoder-only model learns latent representations of input text similar to an encoder but in a more flexible, autoregressive way. | ||
| === 유사도 Encoder === | === 유사도 Encoder === | ||