MTEB: Massive Text Embedding Benchmark

PL-MTEB: Polish Massive Text Embedding Benchmark

OCR, extract and classify documents. In addition, annotate documents and build your own NLP and Computer Vision models using Python by downloading the data. Find examples in our Colab Notebooks, e. g. how to fine-tune Flair.

State of the Art Natural Language Processing

Welcome to InterviewX, your ultimate interview companion powered by AI. With features like scam detection, resume optimization, real-time posture analysis, time-saving text summarization, and ice breaker insights, InterviewX equips you with everything you need to ace your next interview with confidence and ease.

NucliaDB, The AI Search database for RAG

Official repository of my Master's Thesis project: "Developing an AI-Powered Voice Assistant for an iOS Payment App"

bert text classification using onnx of(bert,albert,roberta,macbert and so on).

Proyek ini dikembangkan untuk melakukan analisis mendalam terhadap sentimen yang muncul terkait penerima KIPK (Kartu Indonesia Pintar Kuliah) berdasarkan cuitan dari X. Tujuan utama adalah untuk mengungkap sejauh mana distribusi penerima KIPK mungkin telah menyasar kelompok yang salah di lingkungan perguruan tinggi.

The main idea for this project is explore a Kaggle dataset about ChatGPT reviews using a NLP approach in order to apply ML models for score reviews predictions. I applied LIME algorithm to evaluate explainability about text classifiers. Should it be possible to apply complex network? Let's try.

A broad, easy and fast framework for machine/deep learning in Go.

Simple and Lightweight Text Classifiers with LLM Embeddings

A library for multi-class and multi-label text classification

A machine learning-based web application to classify emails as spam or not spam.

Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.

Train a SetFit model for use in text classification.

ULMFiT Model that classifies swahili news articles

Resources for Master TAL (NLP), first degree, at Inalco.

Resources to learn how to manage corpus with Python.

This collection features a series of NLP projects, covering diverse aspects. Explore projects in text processing, sentiment analysis, entity resolution, and more.