IP屬地：江西
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LLaMA：開(kāi)源的高效的基礎(chǔ)語(yǔ)言模型LLaMA: Open and Efficient Foundation Language Models Feb 2023 Hugo Touvr...
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2025-06-09
使用檢查點(diǎn)支持容錯(cuò)訓(xùn)練 在整個(gè)RLHF訓(xùn)練過(guò)程中，可能會(huì)出現(xiàn)訓(xùn)練錯(cuò)誤或機(jī)器故障，因此建議啟用檢查點(diǎn)功能以最小化損失。 API接口已在 :ref:...
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縮放律與模型架構(gòu)：歸納偏置如何影響縮放？
Scaling Laws vs Model Architectures: How does Inductive Bias Influence S...
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UL2：統(tǒng)一語(yǔ)言學(xué)習(xí)范式
UL2: Unifying Language Learning Paradigms https://arxiv.org/abs/2205.051...
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用0.1%的額外計(jì)算超越縮放定律
Transcending Scaling Laws with 0.1% Extra Compute https://arxiv.org/abs/...
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大語(yǔ)言模型的涌現(xiàn)能力
Emergent Abilities of Large Language Models https://arxiv.org/abs/2206.0...
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預(yù)訓(xùn)練指南：測(cè)量數(shù)據(jù)年齡、領(lǐng)域覆蓋率、質(zhì)量和毒性的影響
A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age...
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自回歸生成建模的縮放律
Scaling Laws for Autoregressive Generative Modeling Oct 2020 https://arx...
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神經(jīng)語(yǔ)言模型的縮放律
Scaling Laws for Neural Language Models Jan 2020 https://arxiv.org/abs/2...