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Trax is a deep learning framework and hardware-agnostic tensor engine designed for designing and training neural networks. It serves as a research tool providing high-level combinators for composing complex architectures, alongside a dedicated library for building transformer models and a toolkit for reinforcement learning. The framework is distinguished by its support for reversible and sparse transformer architectures, which reduce memory and computational overhead. It enables a single set of model instructions to execute across different hardware backends without changing the underlying co
Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
Starspace is a vector embedding framework designed for training high-dimensional representations of text and images. It functions as a machine learning system for neural ranking, text classification, and knowledge graph embedding, mapping different object types into a shared numerical space to facilitate retrieval and prediction tasks. The system includes specialized tools for knowledge graph completion and link prediction by representing entities and their relationships within a multi-relational vector space. It further provides capabilities for semantic content recommendation and large-scal
This project is a high-performance library for converting raw text into tokens and IDs for machine learning models. It functions as a fast text encoder and a text preprocessing pipeline designed to transform strings into numerical representations with high throughput for research and production. The library includes a subword tokenizer trainer used to analyze text datasets and create custom vocabularies using algorithms such as byte-pair encoding and wordpiece. It provides capabilities for subword vocabulary training and text alignment, allowing character offsets to be tracked during normaliz
FACTORIE is a toolkit for deployable probabilistic modeling, implemented as a software library in Scala. It provides its users with a succinct language for creating relational factor graphs, estimating parameters and performing inference.
The main features of factorie/factorie are: Machine Learning Frameworks, Natural Language Processing.
Projects with overlapping indexed features include: guillaume-be/rust-bert — Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...). johnsnowlabs/spark-nlp — Spark NLP is a toolkit for scalable text analysis and machine learning built on the Apache Spark distributed computing… facebookresearch/starspace — Starspace is a vector embedding framework designed for training high-dimensional representations of text and images.… google/trax — Trax is a deep learning framework and hardware-agnostic tensor engine designed for designing and training neural… huggingface/tokenizers — This project is a high-performance library for converting raw text into tokens and IDs for machine learning models. It… pytorch/audio — Data manipulation and transformation for audio signal processing, powered by PyTorch.