Search Results for "memory" - Page 13
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Showing 2490 open source projects for "memory"
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Objeck
Objeck is a modern object-oriented programming language
General-purpose object-oriented and functional programming language. Designed to be intuitive, lightweight, cross-platform and fast. The Objeck compiler produces two types of binaries. The first is an executable and the second type is a library. Libraries can be linked into executables by passing the names of libraries to the compiler. Objeck can be built for a variety of targets. The language is implemented in C++, assembly (i.e., generated machine code) and assisted by code generators for... -
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AWS GenAI LLM Chatbot
A modular and comprehensive solution to deploy a Multi-LLM
...A major part of the design is its RAG layer, which enables the chatbot to pull contextual knowledge from connected data sources so responses can be grounded in enterprise content rather than relying only on model memory. -
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IronClaw
IronClaw is OpenClaw inspired but focused on privacy & security
...IronClaw runs untrusted tools inside isolated WebAssembly (WASM) sandboxes with strict capability-based permissions. It supports multiple interaction channels, including REPL, HTTP webhooks, Telegram, Slack, and a real-time web gateway. With dynamic tool building, persistent memory, and background automation, IronClaw is built to securely expand and adapt to your personal and professional workflows. -
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SAM 2
The repository provides code for running inference with SAM 2
...It retains the core promptable interface—accepting points, boxes, or masks—but incorporates architectural and training enhancements to produce higher-fidelity masks, better boundary adherence, and robustness to complex scenes. The updated model is optimized for faster inference and lower memory use, enabling real-time interactivity even on larger images or constrained hardware. SAM2 comes with pretrained weights and easy-to-use APIs, enabling developers and researchers to integrate promptable segmentation into annotation tools, vision pipelines, or downstream tasks. The project also includes scripts and notebooks to compare SAM2 against SAM on edge cases, benchmarks showing improvements, and evaluation suites to measure mask quality metrics like IoU and boundary error. -
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DGL
Python package built to ease deep learning on graph
Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. -
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FlexLLMGen
Running large language models on a single GPU
...The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on commodity hardware. The architecture distributes computation and memory usage across the GPU, CPU, and disk in order to maximize the number of tokens processed during inference. This design allows organizations to deploy powerful language models for high-volume tasks without the infrastructure costs typically associated with large-scale AI systems. ... -
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KVCache-Factory
Unified KV Cache Compression Methods for Auto-Regressive Models
...In large language models, the key-value cache stores intermediate attention states that enable efficient token generation during inference, but these caches can consume large amounts of GPU memory when handling long contexts. KVCache-Factory provides a platform for implementing and evaluating multiple compression strategies that reduce memory usage while preserving model performance. The framework integrates several state-of-the-art methods such as PyramidKV, SnapKV, H2O, and StreamingLLM, allowing researchers to compare and experiment with different approaches within the same environment. ... -
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uzu
A high-performance inference engine for AI models
...The engine implements a hybrid architecture in which model layers can be executed either as custom GPU kernels or through Apple’s MPSGraph API, allowing it to balance performance and compatibility depending on the workload. By utilizing Apple’s unified memory architecture, uzu reduces memory copying overhead and improves inference throughput for local AI workloads. The system includes a simple high-level API that enables developers to run models, create inference sessions, and generate outputs with minimal configuration. -
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PowerInfer
High-speed Large Language Model Serving for Local Deployment
...Its architecture exploits the observation that only a subset of neurons in large models are frequently activated, allowing the system to preload frequently used neurons into GPU memory while processing less common activations on the CPU. This hybrid execution strategy significantly reduces memory bottlenecks and improves overall inference speed. PowerInfer incorporates specialized algorithms and sparse operators to manage neuron activation patterns and minimize data transfers between hardware components. As a result, it enables powerful language models to run on consumer hardware while achieving performance comparable to more expensive server-grade systems. -
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Vince's CSV Parser
A modern C++ library for reading, writing, and analyzing CSV
...Furthermore, I wanted support for special use cases such as calculating statistics on very large files. With the deluge of large datasets available, a performant CSV parser is a necessity. By using overlapped threads, memory-mapped IO, and efficient data structures, this parser can quickly tackle large CSV files. Furthermore, this parser has a minimal memory footprint and can handle larger-than-RAM files. -
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ants
ants is a high-performance and low-cost goroutine pool in Go
...Abundant APIs: submitting tasks, getting the number of running goroutines, tuning capacity of pool dynamically, releasing pool, rebooting pool. Handle panic gracefully to prevent programs from crash. Efficient in memory usage and it even achieves higher performance than unlimited goroutines in Golang. Nonblocking mechanism. Just take a imagination that your program starts a massive number of goroutines, resulting in a huge consumption of memory. To mitigate that kind of situation, all you need to do is to import ants package and submit all your tasks to a default pool with fixed capacity, activated when package ants is imported. -
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Glow OS
System Analysis Software
Glow is an educational, hobbyist operating system written in C and Assembly, developed to help learners understand the internals of OS design and kernel development. Targeting x86_64 systems, Glow features its own kernel, bootloader, and minimal userland. With clear code structure and a simple design, it serves as a playground for experimenting with low-level systems programming, boot sequences, interrupt handling, and basic UI components like shells and text rendering. -
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CowAgent
AI assistant based on large models that can actively think and plan
...It enables automated message handling by connecting WeChat accounts with AI models that can generate contextual replies, process voice messages, and produce images directly inside chats. The platform has evolved beyond a simple chatbot into a more autonomous agent capable of planning complex tasks, maintaining long-term memory, and invoking external tools to complete workflows. It supports multi-turn conversations with per-user context tracking, allowing more natural and persistent interactions across private and group chats. Developers can extend functionality through a plugin architecture and customizable rules, making it suitable for both personal assistants and enterprise automation scenarios. -
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FastbuildAI
An open-source AI framework for developers and entrepreneurs
...It emphasizes fast iteration: you describe tasks declaratively, wire up tools with typed schemas, and let the runtime handle planning, retries, and result aggregation. The project leans into reproducibility with run records, seed control, and structured traces so you can compare behaviors across versions and inputs. Prompt and memory management are treated as first-class concerns, enabling short-lived scratchpads for reasoning as well as long-horizon state when an agent operates over multiple sessions. The codebase favors small, composable pieces—executors, routers, guards—so teams can adopt just what they need instead of buying into a monolith. It is equally comfortable running locally for development or behind a simple API for production bots and automation workflows. -
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Pyreft
ReFT: Representation Finetuning for Language Models
PyreFT is a tool by Stanford NLP for fine-tuning transformer models with an emphasis on efficient, resource-conserving training and customizability for NLP tasks. -
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fluentbit
Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX
Fluent Bit is a super-fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments. A robust, lightweight, and portable architecture for high throughput with low CPU and memory usage from any data source to any destination. Proven across distributed cloud and container environments. Highly available with I/O handlers to store data for disaster recovery. Granular management of data parsing and routing. Filtering and enrichment to optimize security and minimize cost. The lightweight, asynchronous design optimizes resource usage: CPU, memory, disk I/O, network. ... -
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DSVPN
A dead simple VPN
...Works pretty much everywhere, including on public WiFi where only TCP/443 is open or reliable. Uses only modern cryptography, with formally verified implementations. Small and constant memory footprint. Doesn't perform any heap memory allocations. Small (~25 KB), with an equally small and readable code base. No external dependencies. Works out of the box. No lousy documentation to read. No configuration file. No post-configuration. Run a single-line command on the server, a similar one on the client and you're done. No firewall and routing rules to manually mess with. ... -
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Fusion
A lightweight, self-hosted friendly RSS aggregator and reader
A lightweight RSS feed aggregator and reader. -
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CUDA Python
Performance meets Productivity
...It integrates tightly with the broader Python GPU ecosystem, including Numba for kernel compilation and CCCL for parallel primitives, allowing developers to write performant code without leaving Python. The toolkit also includes utilities for profiling, memory management, distributed computing, and numerical operations, making it suitable for scientific computing, AI, and data processing workloads. -
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FramePack
Lets make video diffusion practical
...The idea is to “pack” frames by detecting shared structure and storing differences efficiently, which can accelerate training or inference on video-like data. By reducing I/O and memory bandwidth, datasets become lighter to load while models still see the essential temporal variation. The repository demonstrates both packing and unpacking steps, making it straightforward to integrate into preprocessing pipelines. It’s useful for diffusion and generative models that learn from sequential image datasets, as well as classical pipelines that batch many related frames. ... -
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RisuAI
Make your own story. User-friendly software for LLM roleplaying
RisuAI (or Risu) is a cross-platform AI roleplay chat application—available as both a desktop and web solution—offering creative story-building and character interaction experiences with support for multiple APIs, in-chat assets, regex capabilities, and more. Supports OpenAI, Claude, Gemini, DeepInfra, Ooba, OpenRouter... and More. Display the image of the current character, according to his/her expressions. Modify model's output by regex, to make a custom GUI and others. -
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EasyR1
An Efficient, Scalable, Multi-Modality RL Training Framework
...The project’s philosophy is practicality: sensible defaults, one-command recipes, and compatibility with popular base models let you stand up experiments without wrestling infrastructure. It emphasizes memory-efficient training strategies so you can train long-context or reasoning-dense models on commodity GPUs. The framework is also organized to help you compare training strategies (e.g., pure SFT vs. preference optimization) so you can see what actually moves metrics in math, code, and multi-step reasoning. For teams exploring open reasoning models, EasyR1 provides an opinionated yet flexible path from dataset to deployable checkpoints. -
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Koog
Koog is the official Kotlin framework for building AI agents
...Ready‑to‑use components address common AI engineering challenges, while intelligent history compression optimizes token usage and preserves context. A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring. -
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ImageSharp
A modern, cross-platform, 2D Graphics library for .NET
...Metadata editing support (IPTC EXIF). Colorspace transforms (RGB/CMYK/Grayscale/CIELab and many more). Over 40 common processing operations. Great performance and memory friendly; work with any dimensions (even hundreds of megapixels). ImageSharp is brimming with features. Common operations are only a few keystrokes away. -
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Open Source Cartridge Reader
A shield for the Arduino Mega that can back up video game cartridges
...Supported cartridge types so far, LoRom, HiRom, ExHiRom, DSP, SuperFX, SuperFX2, SDD1, CX4, SPC7110, SA1 (last two chips need Adafruit Clock Generator). Reads and writes SNES Satellaview 8M Memory packs (BS-X cartridge and Adafruit Clock Generator needed). Reads and writes Nintendo Power Super Famicom Memory Flash Cartridges (needs Adafruit Clock Generator for best result).
