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This is the official PyTorch implementation for the paper "Gated Associative Memory: A Parallel O(N) Architecture for Efficient Sequence Modeling" by Rishiraj Acharya.
DigitalPlat FreeDomain: Free Domain For Everyone
Capture all information throughout your model's development in a reproducible way and tie results directly to the model code!
Embedding Atlas is a tool that provides interactive visualizations for large embeddings. It allows you to visualize, cross-filter, and search embeddings and metadata.
UMAP (Uniform Manifold Approximation and Projection) in Rust
⏩ Ship faster with Continuous AI. Build and run custom agents across your IDE, terminal, and CI
QuantStart.com - QSTrader backtesting simulation engine.
talipp - incremental technical analysis library for python
A Python async and event driven framework for algorithmic trading, with a focus on crypto currencies.
Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"
Simple frontend for LLMs built in react-native.
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are commi…
The accompanying code for "Memory-efficient Transformers via Top-k Attention" (Ankit Gupta, Guy Dar, Shaya Goodman, David Ciprut, Jonathan Berant. SustaiNLP 2021).
The Transformer model implemented from scratch using PyTorch. The model uses weight sharing between the embedding layers and the pre-softmax linear layer. Training on the Multi30k machine translati…
Ranger deep learning optimizer rewrite to use newest components
A concise but complete full-attention transformer with a set of promising experimental features from various papers
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
Implementation of MEGABYTE, Predicting Million-byte Sequences with Multiscale Transformers, in Pytorch
StableSwarmUI, A Modular Stable Diffusion Web-User-Interface, with an emphasis on making powertools easily accessible, high performance, and extensibility.
Upscaling stable diffusion latents using a small neural network.
The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.