Showing 1-19 of 19 projects
RWKV is an RNN-based language model with high performance, fast training, and flexible transformer-like architecture.
A comprehensive library of text classification models and techniques built with deep learning.
A collection of important graph embedding, classification and representation learning papers with implementations for vibe coders.
A TensorFlow implementation of the Transformer, a popular deep learning model for natural language processing tasks.
A Python library that implements Graph Attention Networks, a powerful neural network architecture for graph-structured data.
A comprehensive collection of research papers on automatic speech recognition, speech synthesis, and related topics.
A PyTorch implementation of the Graph Attention Network model for developers working with AI tools.
A PyTorch tutorial for building an image captioning model using the Show, Attend, and Tell technique.
High-performance vector graph neural network database in Rust for real-time AI inference and graph ML.
An open-source library for multilingual automatic speech recognition with word-level timestamps and confidence.
A chatbot framework for the finance and legal domains, with NLU, NLG, and knowledge graph capabilities.
A curated list of attention modules and plug-and-play modules for computer vision in Python.
Sockeye is a PyTorch-based sequence-to-sequence framework for neural machine translation tasks.
A Python library implementing various self-attention mechanisms for computer vision tasks.
A deep learning library for EEG tasks classification, built with TensorFlow.
A curated list of NLP resources focused on Transformer networks, attention mechanism, and large language models.
A PyTorch implementation of the original Transformer model with interactive visualizations.
A text classifier library that uses Hierarchical Attention Networks for document classification.
A comprehensive benchmark for spatio-temporal predictive learning, with a focus on AI-powered weather forecasting and video prediction.
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