Nomic alternatives for AI agents.

Retrieval and Retrieval-augmented LLMs

100+ Chinese Word Vectors 上百种预训练中文词向量

Bringing BERT into modernity via both architecture changes and scaling

Implementation of the node2vec algorithm.

text2vec, text to vector. 文本向量表征工具，把文本转化为向量矩阵，实现了Word2Vec、RankBM25、Sentence-BERT、CoSENT等文本表征、文本相似度计算模型，开箱即用。

Pre-trained subword embeddings in 275 languages, based on Byte-Pair Encoding (BPE)

The Clay Foundation Model - An open source AI model and interface for Earth

Fast State-of-the-Art Static Embeddings

Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).

Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.

Implementation of triplet loss in TensorFlow

Solves basic Russian NLP tasks, API for lower level Natasha projects

Fuzzy string matching, grouping, and evaluation.

GPT-vup BIliBili | 抖音 | AI | 虚拟主播

Privacy-respecting metasearch engine

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.