Search Results for "memory" - Page 99
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Showing 2497 open source projects for "memory"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Performance Info Service is a small configurable applet that displays performance counter data such as CPU usage, page file, system, physical memory usage, ip address, computer name, process/thread count, and system uptime on Windows NT and 2000.
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The JCS is a caching system for distributed java applications. It uses a combination of memory, disk, lateral, and remote components to provide data integrity and session failover across webservers.
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The purpose of snmpwatch is to remotely watch via SNMP the size and the memory used by each process. Snmpwatch will warn you if a process exceeds its `quota' of CPU or memory, theses limits are based on process and host name.
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Chasm is a language using assembler meat with C style bone. It provide the C style flow control statement to make assembler code easier to write and easier to maintain. All the register/memory modify code is in the assembler, give the programmer the de
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platform-indepent libraries which provide i.e. virtual filesystem, reference counting memory manager, common abstract datatypes, config file management, dynamic module loader, ...
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phpServer (based on phpSystem) is a php script designed to give the user information about their system in an easy to read format, from any internet connected computer, such as kernel, uptime, memory and swap and partition space. Additional network-centr
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A debuging library for C++. It does dynamic memory management with malloc and looks for potentiazl problems and leaks. It can also free up all leaked memory at the end of the program. I am currently working on hooking the new and delete keywords to wor
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An experimental windowing system that runs on the Linux framebuffer driver. Aimed at low memory Linux systems, like handhelds. The first public release includes draggable windows and a simple image viewer.
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Nemotron 3
Large language model developed and released by NVIDIA
...It is the post-trained and FP8-quantized variant of the Nemotron 3 Nano model, meaning its weights and activations are represented in 8-bit floating point (FP8) to dramatically reduce memory usage and computational cost while retaining high accuracy. The base Nano architecture uses a hybrid Mamba-Transformer Mixture-of-Experts (MoE) design, allowing the model to activate only a small fraction of its 31.6 billion parameters per token, which improves speed and efficiency without sacrificing quality on complex queries. ... -
Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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Nemotron 3 Super
Open language model developed by NVIDIA as part of Nemotron-3 family
...The model contains approximately 120 billion parameters, but employs a Mixture-of-Experts architecture that activates only a smaller subset of parameters during inference, improving computational efficiency while maintaining high capability. Its architecture combines Transformer attention layers with Mamba state-space components to balance long-context reasoning, memory efficiency, and high-quality language generation. The model is optimized for building AI agents that must perform complex tasks such as planning, tool usage, coding assistance, and multi-step reasoning. -
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Simple Portable Memory Management (SPMM) is a small, easy to integrate memory management library for C++. The library emphasizes simplicity of use and implementation while guaranteeing leak free program execution.
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Test Connect provides monitoring and trend tracking of memory, CPU, etc. on kernel level code on multiple platforms. Used with every build Test Connect can provide insight into how code is behaving, or misbehaving, with system resources or memory.
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Laguna XS.2
Open agentic coding model optimized for local deployment
...The model contains 33B total parameters with only 3B activated per token, allowing it to deliver strong coding performance while remaining efficient enough to run locally on modern consumer hardware. It uses a hybrid attention architecture that combines Sliding Window Attention and global attention layers, reducing memory requirements and improving inference speed. Laguna XS.2 supports native reasoning with interleaved thinking between tool calls, enabling more capable autonomous coding agents and multi-step workflows. The model features a 262K-token context window, preserved reasoning across interactions, FP8 KV-cache optimization, and compatibility with local deployment ecosystems such as Ollama and vLLM. -
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gpt-oss-20b
OpenAI’s compact 20B open model for fast, agentic, and local use
GPT-OSS-20B is OpenAI’s smaller, open-weight language model optimized for low-latency, agentic tasks, and local deployment. With 21B total parameters and 3.6B active parameters (MoE), it fits within 16GB of memory thanks to native MXFP4 quantization. Designed for high-performance reasoning, it supports Harmony response format, function calling, web browsing, and code execution. Like its larger sibling (gpt-oss-120b), it offers adjustable reasoning depth and full chain-of-thought visibility for better interpretability. It’s released under a permissive Apache 2.0 license, allowing unrestricted commercial and research use. ... -
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mms-300m-1130-forced-aligner
CTC-based forced aligner for audio-text in 158 languages
...The model enables accurate word- or phoneme-level timestamping using Connectionist Temporal Classification (CTC) emissions. Unlike other tools, it provides significant memory efficiency compared to the TorchAudio forced alignment API. Users can integrate it easily through the Python package ctc-forced-aligner, and it supports GPU acceleration via PyTorch. The alignment pipeline includes audio processing, emission generation, tokenization, and span detection, making it suitable for speech analysis, transcription syncing, and dataset creation. ... -
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RELICS Distributed Intelligence Platform
Open-source decentralized peer-to-peer intelligence community
...The RELICS platform is the keystone software application that connects and harmonizes all operations of the intelligence process using both human intelligence and biologically inspired learning algorithms to perform intelligence tasks. RELICS users are connected on a peer-to-peer network forming a community intended to meet the high demands of processing, memory, scalability and fault tolerance. All RELICS users must also be providers who contribute to the community resource pool. This may include memory, processing, bandwidth or human resources. The RELICS concept is unprecedented as it is the first system of its kind, and stands in a class alone. It is not finished concept, but a vision that will be shaped by future participants. -
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CopperLang
Embeddable interpreted scripting language for C++ projects
Copper is a lightweight scripting language intended for embedding in C++ applications. It is free of system-specific dependencies and written in cross-platform, version-agnostic C++. It is easy to setup and easy to learn. It uses stack-based, safe memory management to avoid the need for a garbage collector. -
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DiffusionGemma
NVFP4 DiffusionGemma model for fast multimodal text generation
...The model supports a 256K-token context window, configurable thinking mode, native function calling, structured JSON output, and multilingual inference across 35+ languages. The NVFP4 quantization reduces weights and activations from 16-bit to 4-bit, lowering disk size and GPU memory needs for vLLM deployment. -
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MiMo-V2.5-Pro
Flagship MoE model for long-context agents and complex coding
...The model supports a 1 million token context window, enabling it to maintain coherence across long workflows involving thousands of tool calls and multi-step reasoning chains. Architecturally, it uses a hybrid attention system combining Sliding Window Attention and Global Attention to significantly reduce memory usage while preserving long-context performance. It also integrates multi-token prediction modules that accelerate inference and improve reinforcement learning efficiency. Trained on around 27 trillion tokens with FP8 mixed precision and refined through supervised fine-tuning, large-scale agentic reinforcement learning, and distillation. -
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DeepSeek-V4-Pro
Flagship MoE model for advanced reasoning, coding, and agents
...The model supports an ultra-long context window of up to 1 million tokens, making it highly suitable for long-document reasoning, large codebases, and complex multi-step tasks. Architecturally, it introduces optimizations to reduce compute and memory costs while improving stability across long sequences. DeepSeek-V4-Pro is positioned as the high-end variant of the V4 family, outperforming most open-source models in areas such as agentic coding, STEM reasoning, and world knowledge, and approaching the performance of leading closed-source systems. It also supports advanced reasoning modes and tool-based workflows, enabling autonomous task execution. -
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...A very simple to use but advance Rules engine . Allows binding of user function to expose them to the Rules engine, various types of arithmatic, bitwise, logical operations etc. Small memory footprint.
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I have started this server because I was unhappy with the documentation and implementation of the server. Memory consumption was too high and the code was badly written and/or confuse.
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This project implements a set class. It is aimed at those who consider the following to be of importance: - Values in the set are, to a high extent, consecutive numbers - Memory footprint is an issue - Small updates to a large set must be efficient
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A Java client for the memcached protocol with a configurable client-side in-process memory cache supporting replacement/eviction strategies (least-recently-used, least-frequently-used, first-in-first-out) designed to provide extremely low-latency lookup.
