Embedding Models Embedding models map high-dimensional data into a lower-dimensional space, which makes the data easier to process and analyze. Text Models Here is a leaderboard, https://huggingface.co/spaces/mteb/leaderboard The leaderboard above gives each model’s score, parameter count, memory usage, vector dimension, maximum tokens, and other information. Below are some commonly used open-source models:

1. Deploying Jumpserver You need a StorageClass ready in advance to store Jumpserver’s data. Besides the database mentioned below, each component — jms-core, jms-web, jms-koko, jms-lion, jms-chen — also needs a PV for storage. 1.1 Deploying MySQL Refer to https://github.com/shaowenchen/ops-hub/blob/main/database/mysql8.yaml to deploy MySQL. You need to adjust the StorageClass field

1. Fat-Tree In 1985, Charles E. Leiserson of MIT invented the Fat-Tree network. As shown in the figure below, a fat-tree network is a binary tree in which bandwidth gradually increases from the root nodes down to the leaf nodes. In August 2008, a group of computer scientists at UC San Diego published a scalable network architecture design that adopted a topology inspired by the fat-tree topology, achieving better scalability than previous hierarchical networks.

1. Data Processing Architecture It is mainly divided into four layers: Processing capability layer: Spark on Kubernetes provides streaming data processing capability Data management layer: Iceberg provides dataset access operations such as ACID and tables Storage layer: Hive MetaStore manages Iceberg table metadata, PostgreSQL serves as the storage backend for

A token is a unit tightly bound to data. It can be used to measure how much corpus is needed to train a model, and also to measure the input and output length at inference time. 1. What a token is A token can be a whole word, a subword,