Search Results for "total text container" - Page 5
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Showing 132 open source projects for "total text container"
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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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PyPedal is a Python module that provides tools for the manipulation of pedigrees, simple visualization of pedigrees, and the calculation of measures of genetic diversity from pedigrees.
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Free Speech Just Pay Shipping
3d peer to peer chatroom where associated pairs of text gravitate
A 3d chatroom where the things people write gravitate toward eachother based on total strength of associations between those short texts. Strength is a competition of who spends the most computing time trying to associate the texts, similar to Bitcoin's "proof of work" system. While there is unlimited space in the system overall, the space around any specific text is limited by 3d space, which drives competition for what people want that text to be associated with. ... -
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term_ CTruck3D
ASCII-Art variant of the CTruck3D _Open truck/car simulator
the ASCII-art variant of the CTruck3D car simulator series by Simon Hasur : a physically very realistic offroad driving simulator (rally ) in which one can drive in total freedom on a piece of terrain, make jumps, turn upside down and whatever ; see CTruck3D _Open and XCTruck3D _Truck for more detailes. this is a variant which displays graphics using only ASCII characters. This is quite instructive as software, expecially if taken in conjuction with the pure X Window System version: in... -
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NamecoinJ
Namecoin GUI in Java
NamecoinJ is a Java based graphical user interface for Namecoin, a peer-to-peer Domain Name System based on Bitcoin technology (a decentralized cryptocurrency). Donations are welcome: BTC: 19o81NGAHpBmVXkfUcxSttwnBsBnLK9hS3, NMC: Mx3hanF6qXywPAyrAU4S14CwXYcMnecaai -
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BitcoinSuite
Bitcoin GUI in Java
BitcoinSuite is a Java based graphical user interface for Bitcoin, a peer-to-peer decentralized cryptocurrency. It is a direct fork of open source project NamecoinJ at http://sourceforge.net/p/namecoinj/. Donations are welcome: BTC: 1PqYXpLLSeAHz3FiZmPcfr451jnzsGgXbc, NMC: N2TFbwpTNhNLeXaBD8FSBbicb6guQNXUiA -
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point-of-sale system written completely in bash. Keeps track of how many items are being sold, customer traffic patterns, income, and more. Generates nice sales reports at end of session, has automatic recovery, and great with screen readers.
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ScriptBox for several terminal (Bash/Konsole) utilities. Current utilities include: sitemap-ripper - merges sitemaps, sitmap-maker - makes sitemaps, url-extractor - extracts URLs, url2hyperlink - makes links of URLs, file splitter - splits files
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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AVL Array is a sequence container (like std::vector or std::list) that allows fast insert/remove AND fast random access. Shiftable Files offers the usual file primitives plus fast insert/remove. Get the latest version via BZR in the Develop section.
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HTML Header Tree is a Mediawiki extension which organizes a page with a container tree according to its headers. Containers with specific headers are given specific styles.
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...The docker site has the information on how to invoke the container, which is based on Fedora 23 and has a texlive stack.
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jHDL,is a total integrated e-learning framework for chatting, shared white board, download material, html editor, web browsing, video conference and web module for registration, scheduling, and administration. Using EJB as middle tier and Struts framewor
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It goal is to connect the smart main engine (R3D) with any other specific engines (ogre3d, ode, scripting..) and world/rules/game/lang data (files, db..) and graphic/text interface. It is like a multiplatform (linux, win, macos ...) game container.
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Kimi K3
Powerful, native multimodal AI agentic model
Kimi K3 is an open-weight, multim is an open-weight, multimodal agentic AI model from Moonshot AI designed for advanced coding, research, reasoning, and knowledge work. Builtodal agentic AI model from Moonshot AI designed for advanced coding, research, reasoning, and knowledge work. Built with 2.8 trillion total parameters and a sparse mixture-of-experts architecture, it activates 104 billion parameters per token to with 2.8 trillion total parameters and a sparse mixture-of-experts architecture, it activates 104 billion parameters per token to deliver frontier-level performance more efficiently. Kimi K3 combines native text and image understanding deliver frontier-level performance more efficiently. -
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DiffusionGemma
NVFP4 DiffusionGemma model for fast multimodal text generation
DiffusionGemma 26B A4B IT NVFP4 is NVIDIA’s Model Optimizer quantized release of Google DeepMind’s DiffusionGemma 26B A4B IT model. It is an open-weights multimodal generative model that processes text, images, and video inputs to produce text output through discrete diffusion. Built on the Gemma 4 26B A4B Mixture-of-Experts architecture, it has 25.2B total parameters and 3.8B active parameters, balancing capability with efficient inference. Its diffusion-based generation produces tokens in parallel 256-token blocks, enabling very high-speed output, with reported generation above 1,100 tokens per second on NVIDIA Hopper H100 in FP8. ... -
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Inkling-Small
Efficient multimodal MoE model for coding, tools, and reasoning
Inkling-Small is an open-weight general-purpose multimodal model from Thinking Machines Lab, designed for agentic systems, coding assistants, chatbots, retrieval workflows, and natural-language applications. It accepts text, images, and audio as input and produces text output, with multilingual and multi-programming-language capabilities. The model uses a sparse Mixture-of-Experts architecture with 276B total parameters and 12B active per token, enabling strong performance with lower inference cost than a fully dense model of similar scale. Its 42-layer decoder routes each token through six of 256 specialized experts plus two shared experts, while hybrid local and global attention supports efficient processing. ... -
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Command A+
4-bit Command A+ model for enterprise agents and multilingual tasks
Command A+ 05-2026 W4A4 is a 4-bit quantized version of Cohere’s open-source Command A+ model, optimized for enterprise-grade agentic, multilingual, and reasoning-heavy workloads. It supports text and image inputs, generates text outputs, and uses a sparse Mixture-of-Experts Transformer architecture with 218B total parameters and 25B active parameters. The W4A4 release applies 4-bit weight and activation quantization mainly to MoE experts, preserving attention components at full precision to reduce quality loss while improving speed, latency, and hardware efficiency. ... -
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Qwen3.6-35B-A3B
Open multimodal model for coding, agents, and long-context tasks
...Architecturally, it uses a Mixture-of-Experts design with 35B total parameters and 3B active, supports a native 262K-token context window, and can be extended to about 1M tokens with YaRN. It also performs strongly across coding, agent, vision, reasoning, and document-understanding benchmarks. -
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GLM-5.3-Flash
Efficient 320B multimodal MoE model for coding and autonomous agents
...GLM-5.3-Flash supports text and image inputs and is particularly optimized for coding and autonomous agent workloads, approaching larger frontier models on related benchmarks while improving over GLM-5.2. It supports local deployment through SGLang, vLLM, TokenSpeed, and KTransformers and is released under the MIT license. -
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MiMo-V2.5
Omnimodal AI model for agents, coding, and long-context tasks
MiMo-V2.5 is a native omnimodal large language model developed by Xiaomi, designed for advanced agentic workflows, multimodal reasoning, and long-context processing. Built on a Mixture-of-Experts architecture with approximately 309B total parameters and around 15B activated per inference, it balances high capability with efficient execution. The model natively processes text, images, video, and audio within a unified system, enabling cross-modal understanding and complex task execution in a single pipeline. With a context window of up to 1 million tokens, it can handle large documents, extended conversations, and multi-step workflows without fragmentation. ... -
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Qwen3.6-35B-A3B-FP8
FP8 Qwen model for efficient multimodal coding and agent tasks
...The model uses a Mixture-of-Experts design with 35B total parameters and 3B active, supports a native context window of 262,144 tokens, and can be extended to about 1,010,000 tokens with YaRN. It is compatible with major inference frameworks such as Transformers, vLLM, SGLang, and KTransformers, making it a practical high-performance option. -
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MiMo-V2.6-Flash
Efficient 309B omnimodal MoE for coding, agents, vision, and audio
MiMo-V2.6-Flash is Xiaomi MiMo’s efficiency-balanced open-weight omnimodal model, designed to scale reinforcement learning across coding, general agents, visual tasks, and cybersecurity. Its sparse Mixture-of-Experts architecture contains 309B total parameters while activating only 15B per token, using 256 routed experts with eight active per token. The model natively processes text, images, video, and audio and supports a 1M-token context window for large repositories, extended tool traces, and multi-session agent workflows. Training uses a unified mixed RL process rather than separate domain-specific runs, alongside asynchronous GRPO and groupwise agentic grading that rewards higher-quality and more efficient solutions. ... -
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MiMo-V2.6-Pro
1T omnimodal MoE model for coding, agents, and long-horizon reasoning
MiMo-V2.6-Pro is Xiaomi MiMo’s flagship open-weight omnimodal model, built to scale reinforcement learning toward self-improvement across coding, agents, vision, and cybersecurity. Its sparse Mixture-of-Experts architecture contains 1.02T total parameters with 42B activated per token, using 384 routed experts with eight active per token. The model natively processes text, images, video, and audio and supports a 1M-token context window for large repositories, extended tool traces, and multi-session agent workflows. MiMo-V2.6-Pro-RL uses a unified mixed reinforcement learning process rather than separate domain-specific runs, alongside groupwise agentic grading that rewards higher-quality and more efficient solutions. ... -
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GLM-4.5-Air
Compact hybrid reasoning language model for intelligent responses
...GLM-4.5-Air supports both English and Chinese, and is suitable for tasks involving text generation, coding, reasoning, and tool calling. Open-sourced under the MIT license, it is commercially usable and integrates with transformers, vLLM, and SGLang inference frameworks. It includes FP8 variants for faster inference and reduced memory requirements. Despite its smaller size compared to full GLM-4.5, GLM-4.5-Air maintains high performance.
