# Academic Literature Clustering

A Japanese-English bilingual sentence feature extraction model based on modernbert-ja-310m, supporting sentence similarity computation and text classification tasks

A 7B-parameter instruction-tuned model based on Qwen2 architecture, specializing in sentence similarity computation and text embedding tasks

stella-base-en-v2 is an English text embedding model based on sentence-transformers, focusing on sentence similarity and feature extraction tasks.

GTE-Base is a general-purpose text embedding model focused on sentence similarity and text retrieval tasks, performing well on multiple benchmarks.

E5-base is a general-purpose text embedding model suitable for various natural language processing tasks such as classification, retrieval, clustering, and semantic similarity calculation.