# Academic literature clustering

Amber Base is a Japanese-English sentence encoder model based on modernbert-ja-130m, specializing in sentence similarity calculation and feature extraction tasks.

A 7B-parameter sentence embedding model based on the Qwen2 architecture, specializing in sentence similarity tasks with outstanding performance on the MTEB benchmark.

NV-Embed-v2 is an embedding model based on sentence-transformers, excelling in multiple MTEB benchmarks and suitable for various natural language processing tasks.

A general-purpose text embedding model developed by Salesforce, excelling in various NLP tasks

LLM2Vec is a supervised learning model based on Meta-Llama-3, focusing on natural language processing tasks such as sentence similarity, and supporting various application scenarios such as text embedding, information retrieval, and text classification.

Snowflake Arctic Embed XS is a lightweight sentence embedding model focused on sentence similarity and feature extraction tasks.

e5-base-4k is a model that performs excellently in multiple natural language processing tasks, especially in tasks such as text classification, retrieval, clustering, and semantic text similarity.

SGPT-Bloom-7b1-msmarco is a sentence transformer model based on the BLOOM architecture, primarily used for sentence similarity calculation and feature extraction tasks.