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#GLiClass is based on uni-encoder transformer architecture that embeds labels and text in the same context enabling better inter-label communication, fixing in this way the main drawback of cross-encoder classifiers.

knowledgator's tweet image. #GLiClass is based on uni-encoder transformer architecture that embeds labels and text in the same context enabling better inter-label communication, fixing in this way the main drawback of cross-encoder classifiers.

🚀 Inspired by #GLiNER we developed #GLiClass - efficient zero-shot classifiers that demonstrate comparable performance to cross-encoders while being faster. Thanks to ModernBERT introduced by @LightOnIO and @answerdotai, we can make our models even more efficient.…


@Monii_GL que pasa que tenemos tres años #gliclass


#GLiClass is based on uni-encoder transformer architecture that embeds labels and text in the same context enabling better inter-label communication, fixing in this way the main drawback of cross-encoder classifiers.

knowledgator's tweet image. #GLiClass is based on uni-encoder transformer architecture that embeds labels and text in the same context enabling better inter-label communication, fixing in this way the main drawback of cross-encoder classifiers.

🚀 Inspired by #GLiNER we developed #GLiClass - efficient zero-shot classifiers that demonstrate comparable performance to cross-encoders while being faster. Thanks to ModernBERT introduced by @LightOnIO and @answerdotai, we can make our models even more efficient.…


@Monii_GL que pasa que tenemos tres años #gliclass


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#GLiClass is based on uni-encoder transformer architecture that embeds labels and text in the same context enabling better inter-label communication, fixing in this way the main drawback of cross-encoder classifiers.

knowledgator's tweet image. #GLiClass is based on uni-encoder transformer architecture that embeds labels and text in the same context enabling better inter-label communication, fixing in this way the main drawback of cross-encoder classifiers.

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