The Visual AI Suite is a comprehensive toolkit designed to deliver cutting-edge AI functionalities for processing and analyzing visual data combined with natural language tasks. The suite integrates three powerful models: Image Description, Question Answering, and Visual Question Answering.

😷 The Fill-Mask Association Test (FMAT): Measuring Propositions in Natural Language.

Sentiment Analysis using IMDB Dataset of 50K Movie Reviews | A Fellowship.AI Code Challenge Submission By me

Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks

This project benchmarks various BERT-based models on the IMDB movie review dataset for sentiment classification, evaluating accuracy, precision, recall, and F1 score.

Hallucination in Chat-bots: Faithful Benchmark for Information-Seeking Dialogue

Arabic Sentiment Analyzer: Integrating State-of-the-Art Pre-trained Sentiment Models ( AraBERT, and AraNet) in a Single Tool.

QBERT-Utilized Edge Speech Technology. AI Voice Assistant

Comparing between residual stream and highway stream in transformers(BERT) .

TRAM: Benchmarking Temporal Reasoning for Large Language Models (Findings of ACL 2024)

OnnxRT based Inference Optimization of Roberta model trained for Sentiment Analysis On Twitter Dataset

A dark web analysis tool.

Simple State-of-the-Art BERT-Based Sentence Classification with Keras / TensorFlow 2. Built with HuggingFace's Transformers.

Accelerating Growth through the DeepBOT Chatbot

Implementation of Protein Classification based on subcellular localization using ProtBert(Rostlab/prot_bert_bfd_localization) model from Hugging Face library, based on BERT model trained on large corpus of protein sequences.

Bert sentence comparison using AI pretrained model.

Hate Speech Detection in Tweets using text and image data

B.Sc. Thesis Deep Learning & NLP research on Medical Image Captioning

A scifi novel search engine, where you can find what to read based on what emotion and topic you want to read about.