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Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
Centromere sequence analysis using rare k-mer markers
A high-performance distributed file system designed to address the challenges of AI training and inference workloads.
Trading bot running on Bybit, Bitget, OKX, GateIO, Binance and Hyperliquid
Implementation of the proposed minGRU in Pytorch
Command and Conquer Tiberian Dawn
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
A fast work-stealing queue template in C++
A General-purpose Task-parallel Programming System using Modern C++
📦 Repomix (formerly Repopack) is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) o…
A Recurrent Convolutional Network Quantifies CRISPR Off-target Activities with Indels and Mismatches
Fast and exact gap-affine partial order alignment
YuE: Open Full-song Music Generation Foundation Model, something similar to Suno.ai but open
Janus-Series: Unified Multimodal Understanding and Generation Models
WinPCA. A package for windowed principal component analysis.
Train transformer language models with reinforcement learning.
Implementation of the paper "Lossless Compression of Vector IDs for Approximate Nearest Neighbor Search" by Severo et al.
LLMap solves context extraction for large codebases
this is based on the paper Were RNNs All We Needed? im trying to create the Simplification of traditional RNNs the key in here is that is removing the hidden state dependencies from their gates.
A step-by-step guide to setting up llama.cpp with ROCm on AMD APUs