https://pypi.org/project/deer-probe/ Recent updates to the Python Package Index for deer-probe en https://pypi.org/project/deer-probe/0.1.1/ DEER is an encoder-based knowledge graph completion (KGC) model that uses embedding vectors from generative language models for few-shot learning. It retains in-context learning while ensuring efficient large-scale inference without fine-tuning. DEER excels at predicting new relation types in small KGs and aligns with LAMA for knowledge probing, making it a scalable tool for evaluating factual knowledge in PLMs. jinno.tomoyuki.jx3@naist.ac.uk Fri, 07 Mar 2025 18:12:21 GMT https://pypi.org/project/deer-probe/0.1.0/ DEER is an encoder-based knowledge graph completion (KGC) model that uses embedding vectors from generative language models for few-shot learning. It retains in-context learning while ensuring efficient large-scale inference without fine-tuning. DEER excels at predicting new relation types in small KGs and aligns with LAMA for knowledge probing, making it a scalable tool for evaluating factual knowledge in PLMs. jinno.tomoyuki.jx3@naist.ac.uk Fri, 07 Mar 2025 18:01:11 GMT