Search Results for "transformer"
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Showing 38 open source projects for "transformer"
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spacy-transformers
Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
...These techniques can be used to import knowledge from raw text into your pipeline, so that your models are able to generalize better from your annotated examples. You can convert word vectors from popular tools like FastText and Gensim, or you can load in any pre trained transformer model if you install spacy-transformers. You can also do your own language model pretraining via the spacy pre train command. You can even share your transformer or another contextual embedding model across multiple components, which can make long pipelines several times more efficient. To use transfer learning, you’ll need at least a few annotated examples for what you’re trying to predict. -
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parcel/css
A CSS parser, transformer, and minifier written in Rust
A CSS parser, transformer, and minifier written in Rust. Parsing and minifying large files are completed in milliseconds, often with significantly smaller output than other tools. Many other CSS parsers treat property values as an untyped series of tokens. This means that each transformer that wants to do something with these values must interpret them itself, leading to duplicate work and inconsistencies. -
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ai-notebooks
Some ipython notebooks implementing AI algorithms
...Projects explore problems such as MNIST learning, GANs, VAEs, model compression, and knowledge distillation. Other notebooks examine reinforcement learning through PPO, SAC, TD3, VPG, and MuZero experiments. Transformer, recurrent-network, counterfactual-regret, and normalizing-flow examples broaden the collection. The notebooks are designed to be read directly on GitHub, making the repository useful for studying algorithms through working code. -
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X For You Feed Algorithm
Algorithm powering the For You feed on X
...The repository contains the full pipeline that ingests user engagement and content candidate data, processes it through retrieval, hydration, filtering, scoring, and selection layers, and ultimately ranks posts to show what appears in a user’s feed. At its heart, the system uses a transformer-based model adapted from xAI’s Grok architecture to predict probabilities for various user actions (such as likes, replies, reposts, clicks, and negative signals), then combines those into a weighted final score that drives ranking. -
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ONNX Runtime
ONNX Runtime: cross-platform, high performance ML inferencing
...ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Support for a variety of frameworks, operating systems and hardware platforms. Built-in optimizations that deliver up to 17X faster inferencing and up to 1.4X faster training. -
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Laravel Data
Powerful data objects for Laravel
This package enables the creation of rich data objects which can be used in various ways. Using this package you only need to describe your data once. -
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SDWebImageSwiftUI
SwiftUI Image loading and Animation framework powered by SDWebImage
SDWebImageSwiftUI is a SwiftUI image-loading framework, which is based on SDWebImage. It brings all your favorite features from SDWebImage, like async image loading, memory/disk caching, animated image playback and performances. The framework provide the different View structs, which API match the SwiftUI framework guideline. If you're familiar with Image, you'll find it easy to use WebImage and AnimatedImage. Since SDWebImageSwiftUI is built on top of SDWebImage, it provide both the... -
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ts-blank-space
A small, fast, pure JavaScript type-stripper
ts-blank-space is a fast type-stripping compiler that converts TypeScript to JavaScript. It supports a modern subset of TypeScript by erasing the types and replacing them with whitespace. That's it. It is not a type checker and does not perform any other code transformations. The underlying technique can improve build performance and simplify development. The implementation is pure TypeScript. It is simple enough to read and understand in a few minutes because it is only 700 lines of code... -
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Laravel Fractal
An easy to use Fractal wrapper built for Laravel and Lumen
...Imagine you want to add some stats to the metadata of your request, you can do so without cluttering your code. You can run the make:transformer command to quickly generate a dummy transformer. By default it will be stored in the app\Transformers directory. -
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained... -
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Transformers4Rec
Transformers4Rec is a flexible and efficient library
Transformers4Rec is an advanced recommendation system library that leverages Transformer models for sequential and session-based recommendations. The library works as a bridge between natural language processing (NLP) and recommender systems (RecSys) by integrating with one of the most popular NLP frameworks, Hugging Face Transformers (HF). Transformers4Rec makes state-of-the-art transformer architectures available for RecSys researchers and industry practitioners. -
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SVGR
Transform SVGs into React components
React supports SVG out of the box, it's simpler, easier and much more powerful to have components instead of SVG files. Wrapped in a React component, your SVG is inlined in the page and you can style it using CSS. SVGR differs from other library by its solid architecture. It uses svg-parser + Babel to transform SVG code into JavaScript code. A whole directory can be processed, all SVG files (matching .svg or .SVG) are transformed into React components. It is possible to target React Native... -
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iJEPA
Official codebase for I-JEPA
...This objective sidesteps generative pixel losses and avoids heavy negative sampling, producing features that transfer strongly with linear probes and minimal fine-tuning. The design scales naturally with Vision Transformer backbones and flexible masking strategies, and it trains stably at large batch sizes. i-JEPA’s predictions are made in embedding space, which is computationally efficient and better aligned with downstream discrimination tasks. The repository provides training recipes, data pipelines, and evaluation code that clarify which masking patterns and architectural choices matter most. -
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Random fun
Notebooks and various random fun
...Included notebooks examine topics such as MicroGrad-style autodiff, mixture density networks, evolution strategies, floating-point behavior, and KNN versus SVMs. Several notebooks explore minimal character-level recurrent neural networks and transformer-related ideas. The repository also contains Rust experiments and lecture material alongside the notebooks. Most of the code is written as self-contained experiments that can be read and modified independently. Its value is primarily educational, showing small implementations of technical concepts without a large framework around them. -
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Polysemy
Higher-order, no-boilerplate monads
Polysemy is a high-performance, zero-boilerplate effect system for Haskell, designed to simplify the handling of side effects in functional programs. Unlike traditional monad transformer stacks, Polysemy uses a modern approach based on freer monads and interpreters, allowing developers to define, compose, and interpret effects in a more modular and testable way. It aims to offer both flexibility and performance without sacrificing type safety or expressiveness. -
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TransPose
PyTorch Implementation for "TransPose, Keypoint localization
TransPose is a human pose estimation model based on a CNN feature extractor, a Transformer Encoder, and a prediction head. Given an image, the attention layers built in Transformer can efficiently capture long-range spatial relationships between keypoints and explain what dependencies the predicted keypoints locations highly rely on. -
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
...By enabling tractable training on longer contexts, the project opened the door to applications in large-scale text and image generation. Though archived, it remains a key reference for efficient transformer research, influencing many later architectures that aim to extend sequence length while reducing compute. -
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DETR
End-to-end object detection with transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. -
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transformer
A TensorFlow Implementation of the Transformer
Transformer is a TensorFlow implementation of the architecture introduced in the Attention Is All You Need paper. It was created as a readable and relatively modular reference for understanding and experimenting with Transformer-based machine translation. The updated implementation corrects issues involving masking, positional encoding, and other parts of the original code. -
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attention
Some attention implements
...Users needing updated implementations are directed toward related layers in the author's bert4keras project. Its main value today is as a concise historical example of early Transformer-style attention code. -
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Mirage
GUI for simplifying Elasticsearch Query DSL
...Mirage is a modern, open-source web-based query explorer for Elasticsearch. It offers a blocks-based GUI for composing Elasticsearch queries and comes with an on-the-fly transformer to show the corresponding JSON query API of Elasticsearch. Queries can be saved for later reuse. They can also be captured and shared by copying the URL. Mirage works with any Elasticsearch 2. x, 5. x, 6. x, and 7.x index currently. Below is the roadmap for query support. Every app in appbase.io has a query explorer view, which uses mirage. ... -
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CSV Comparator
CSV Comparator is a tool for comparing files which contain CSV-Data.
...There is a command line tool as well as a user interface. In case you need to compare .xml-Files you can convert them to .csv-Files with my other project CSV Transformer. The advantages by using CSV as input and output are the following: - Many applications allow an export of its data to CSV or Excel(were it could be saved to CSV) - It is possible to pre- and postprocess the data, e.g removing version numbers before comparing - It is easy to create CSV data from logfiles and other resources by using unix tools like sed or awk - CSV can be loaded into other applications, especially Excel, were it can be formatted by macros for analyzing. -
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CSV Transformer
transforms xml to csv
The CSV Transformer is a data processing tool which transforms .xml-Files to comma separated values. The CSV Transformer was created in a load and performance testing project, the use case was to be able to transform 2800 configuration files of a big banking application to a single .csv-File. With this single file it was possible to compare the whole configuration between two releases with the already available tool CSV Comparator. -
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PLUTO is an automatic source-to-source transformer that can optimize nested loop sequences for coarse-grained parallelism and cache locality simultaneously. OpenMP parallel code for multicores can be generated from regular C program sections. Version
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HL7 to XML Transformation toolkit. Using HL7 v2 XML
