Implementations of Popular Static Word Embedding Techniques
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Updated
Jun 5, 2025 - Jupyter Notebook
Implementations of Popular Static Word Embedding Techniques
Lightweight Semantic Chunking Library. Plug any embedding provider/API. Batch embeddings for efficiency and handling API rate limits.
RemEz is a descriptive question based learning platform built for students in highly theoretical subjects. The Frontend and Backend of this platform is built with the MERN stack and tailwind. This repository contains nlp code for pdf processing and descriptive QA generation via a LLM along with a similarity assessment of two descriptive answers.
Sentence Transformer model fine tuned on mtsb dataset to generate embeddings of Nepali sentences. Try from here:
VectorLite is a Rust-native, in-process vector store that brings sub-millisecond search and local embeddings to your AI agents and edge systems.
Dockerized application that embeds text in a pgvecto.rs database and retrieves data with a similarity search to generate a response with an llm from ollama.
Simple, cross-platform port of GloVe embeddings, written in C
RoleRadar turns free-form requests like “Data Analyst roles in New York with SQL experience.” into structured filters and semantic-vector queries, delivering spot-on matches in seconds.
Word Mini-Game : Guess the secret word ! Play here :
Learning project: modular RAG pipeline for legal document search & Q&A using SBERT, Pinecone, and FastAPI.
Contextual Code Exploration for Developers
Data Collection repository for Reverse Search Engine
RAG Mini Project — Retrieval‑Augmented Generation chatbot with FastAPI backend (Docker on Hugging Face Spaces) and Streamlit frontend (Render), featuring document ingestion, vector search, and LLM‑powered answers
Python library for correcting registry and spelling errors in user input when comparing with a database of texts.
Building an Event Retrieval System from Visual Data participating in Ho Chi Minh's AI Challenge in 2024
KektorDB is an in-memory vector database built from scratch in Go. It provides an HNSW-based engine for approximate nearest neighbor search, metadata filtering, and a JSON-based REST API.
A Python dictionary that uses semantic similarity for key matching instead of exact matches. This library allows you to retrieve values using keys that are semantically similar to the ones stored, making it ideal for natural language interfaces, etc.
A noob's guide to AI Agents and RAG implementation using mistral-ai
Sentiment analysis using machine learning classifiers SVM and MLP to investigate potential gender biases in the provided dataset.
AI song recommendations based on the feel of a song
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