Search Results for "transformer"
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Showing 10 open source projects for "transformer"
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1
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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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. -
4
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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5
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. -
7
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. -
8
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. -
9
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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10
Simple Yaml2Java Transformer
Provides quick transformation from yaml to Java Objects
Provides quick transformation from .yaml or .yml files in classloader or filesystem to java class instances. GitHub: https://github.com/DeMmAge/Simple-Yaml-Transformer Library based on snakeyaml: https://mvnrepository.com/artifact/org.yaml/snakeyaml Add Jitpack repository in <repositories> section in pom.xml: <repositories> <repository> <id>jitpack.io</id> <url>https://jitpack.io</url> </repository> </repositories> Add Simple-Yaml-Transformer dependency: <dependency> <groupId>com.github.DeMmAge</groupId> <artifactId>Simple-Yaml-Transformer</artifactId> <version>1.0.0</version> </dependency>
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