div class=ts-pagebuttonPage 1button div class=ts-image amp-img class=ts-thumb alt=Page 1: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails1jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 2button div class=ts-image amp-img class=ts-thumb alt=Page 2: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails2jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 3button div class=ts-image amp-img class=ts-thumb alt=Page 3: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails3jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 4button div class=ts-image amp-img class=ts-thumb alt=Page 4: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails4jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 5button div class=ts-image amp-img class=ts-thumb alt=Page 5: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during 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theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails10jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 11button div class=ts-image amp-img class=ts-thumb alt=Page 11: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails11jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 12button div class=ts-image amp-img class=ts-thumb alt=Page 12: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during 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Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails17jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 18button div class=ts-image amp-img class=ts-thumb alt=Page 18: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails18jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 19button div class=ts-image amp-img class=ts-thumb alt=Page 19: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during 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Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails24jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 25button div class=ts-image amp-img class=ts-thumb alt=Page 25: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during src=https:reader033vdocumentsnetreader033viewer20220518065ffe12bceba59b2b3e264a24html5thumbnails25jpg width=142 height=106 layout=responsive amp-img divdivdiv class=ts-pagebuttonPage 26button div class=ts-image amp-img class=ts-thumb alt=Page 26: Microsoft · PYIX = Strong: Autoregressive model eg Transformers can in theory model any arbitrary distribution Of sequences Slow: we need to predict one word and a time during 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