Trained Models from "General Cross-Architecture Distillation of Pretrained Language Models into Matrix Embeddings"
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下载链接：
https://zenodo.org/record/6533888
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资源简介：
Trained models from the paper:
Lukas Galke, Isabell Cuber, Christoph Meyer, Henrik Ferdinand Noelscher, Angelina Sonderecker, and Ansgar Scherp: General Cross-Architecture Distillation of Pretrained Language Models into Matrix Embeddings, in: International Joint Conference on Neural Networks (IJCNN), 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
创建时间：
2022-05-11
