Trained Models from "General Cross-Architecture Distillation of Pretrained Language Models into Matrix Embeddings"
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Trained models from the paper: Lukas Galke, Isabell Cuber, Christoph Meyer, Henrik Ferdinand Noelscher, Angelina Sonderecker, and Ansgar Scherp: <strong>General Cross-Architecture Distillation of Pretrained Language Models into Matrix Embeddings</strong>, in: <em>International Joint Conference on Neural Networks (IJCNN), </em>2022. File seq2mat_hybrid_bidirectional_sbertlike-100p-bsz512 holds the model from pretraining File ws2020_transformer_final_models holds the fine-tuned models for each task of the GLUE benchmark
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Zenodo创建时间：
2022-05-11
