attention-mechanism

several types of attention modules written in PyTorch for learning purposes

A repository containing comprehensive Neural Networks based PyTorch implementations for the semantic text similarity task, including architectures such as: Siamese LSTM Siamese BiLSTM with Attention Siamese Transformer Siamese BERT.

Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch

Implementation of Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer in PyTorch.

Flexible Python library providing building blocks (layers) for reproducible Transformers research (Tensorflow ✅, Pytorch 🔜, and Jax 🔜)

Physics-inspired transformer modules based on mean-field dynamics of vector-spin models in JAX

An implementation of Conformer: Convolution-augmented Transformer for Speech Recognition, a Transformer Variant in TensorFlow/Keras

The notebook explains the various steps to obtain the results of publication: "Is Space-Time Attention All You Need for Video Understanding?"

A curated list of recent papers (2023–2025) on controllable generative models, covering diffusion-based architectures with fine-grained control, attention interpretation, spectral manipulation, and structure-preserving image editing. Ideal for researchers and developers exploring controllable synthesis.

End-to-end pipeline for seeing how LLMs actually process your prompts. Capture attention across every layer, render heatmaps and cooking curves, compare variants with evidence — not vibes.

AthenaOS is a next generation AI-native operating system managed by Swarms of AI Agents

The open source implementation of the cross attention mechanism from the paper: "JOINTLY TRAINING LARGE AUTOREGRESSIVE MULTIMODAL MODELS"

Build a Large Language Model From Scratch

Natural Language Processing Nanodegree from Udacity Platform, in which I implement Hidden Markov Model for POS Tagger, Bidirectional LSTM for English-French Machine Translation, and End-to-End LSTM-based Speech Recognition

Implementation of build an LLM from scratch by Sebastian Raschka.

Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affective computing. The technique and results of our team, UTNLP, in the SemEval-2022 shared task 6 on sarcasm detection are presented in this paper.

The open source implementation of the multi grouped query attention by the paper "GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints"

Python framework for artificial text detection: NLP approaches to compare natural text against generated by neural networks.

Empower Truly Autonomous AI Agents through our Experimental Adversarial and Evolutionary Reinforcement Learning Framework. Join our Community: https://t.me/evolveRL_portal

The repository for the exclusive Daily Paper Club hosted at Agora every 10pm NYC time at this discord: https://discord.gg/Gnzh6dnzyz