A curated list of pretrained sentence and word embedding models
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Updated
Apr 23, 2021 - Python
A curated list of pretrained sentence and word embedding models
Python library for knowledge graph embedding and representation learning.
Implementations of Embedding-based methods for Knowledge Base Completion tasks
Plugin that creates a vector database to do RAG to work with LM Studio running in server mode!
Image search engine
Word Embeddings for Information Retrieval
Neural Code Comprehension: A Learnable Representation of Code Semantics
Web-ify your word2vec: framework to serve distributional semantic models online
tensorflow prediction using c++ api
ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embedding. The project objective is to develop an ecosystem to experiment, share, reproduce, and deploy in real-world in a smooth and easy way.
langchain-chat is an AI-driven Q&A system that leverages OpenAI's GPT-4 model and FAISS for efficient document indexing. It loads and splits documents from websites or PDFs, remembers conversations, and provides accurate, context-aware answers based on the indexed data. Easy to set up and extend.
A monolingual and cross-lingual meta-embedding generation and evaluation framework
Generates a set of property-specific entity embeddings from knowledge graphs using node2vec
A binary analysis tool for identifying unknown function names, using a word-2-vec model
Learning node representation using edge semantics
PyTorch implementation of paper "Visual Concept-Metaconcept Learner", NeruIPS 2019
Representation Learning for the Automatic Indexing of Sound Effects Libraries (ISMIR 2022): Deep audio embeddings pre-trained on UCS & Non-UCS-compliant datasets.
Code and resources showcasing the Retrieval-Augmented Generation (RAG) technique, a solution for enhancing data freshness in Large Language Models (LLMs). Incorporate up-to-date external knowledge into LLM-generated responses. Additionally, this repository includes a Gradio-based user interface for seamless model deployment.
Code for paper: Learning to Build User-tag Profile in Recommendation System
GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embeddings
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