Search Results for "utf-8" - Page 77
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Showing 1946 open source projects for "utf-8"
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Nemotron 3
Large language model developed and released by NVIDIA
NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 is a state-of-the-art large language model developed and released by NVIDIA as part of its Nemotron 3 family, optimized for high-efficiency inference and strong reasoning performance in open AI workloads. 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. ... -
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Qwen3.8-27B
Dense 27B multimodal model for coding, agents, and visual reasoning
Qwen3.8-27B is a compact, open-weight dense multimodal model designed for advanced coding, professional work, research, visual understanding, and long-horizon agentic tasks. Built on the Qwen3.5 architecture, it contains 27B parameters and combines Gated DeltaNet with gated attention across 64 layers. The model natively understands text, images, and videos, including documents, STEM diagrams, and hour-scale video content. Agent capabilities emphasize autonomous planning, environment... -
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Win2Lin is a program to convert your windows encoded files "windows-1252" to "utf-8" which is the standard encoding for linux
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Qwen3.8-Flash-Next
Efficient multimodal MoE model for coding, reasoning, and AI agents
Qwen3.8-Flash-Next is Qwen’s experimental open-weight multimodal model previewing the architecture planned for Qwen4. It uses 125B language-model parameters with only 6B activated per token, supplemented by 51B n-gram embedding parameters and 4B for multi-token prediction. Its hybrid architecture combines Gated DeltaNet with Qwen Sparse Attention (QSA), which processes micro-blocks rather than individual tokens to reduce latency in long-context agent workloads. The model also introduces... -
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SimpleCompiler
Tools for creating code generators.
SimpleCompiler is a suite of tools for generating compilers and code generators. A simple BNF style language is used to describe scanner and parser in a UTF-8 source file. The output is described with a template language that is used to add formatting to the parse tree. Code is generated that automatically traverses the parse tree and calls a method on a transformer object to modify the parse tree. Each node is visited in document order, and a method is called at the beginning and end of each node visit. ... -
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Qwen3.8-2.4T-A95B
Massive 2.4T MoE model for coding, agents, research, and reasoning
Qwen3.8-2.4T-A95B is Qwen’s largest open-weight model and the first Qwen-Max-class model released openly, targeting advanced coding, professional work, research, and long-horizon agentic tasks. It uses a massive Mixture-of-Experts architecture with 2.4 trillion total parameters while activating 95B per token, combining Gated DeltaNet and attention layers across 512 experts. The model emphasizes reliable autonomous execution, including stronger planning, environment feedback handling, and... -
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java-tutorial-spanish
Oracle Java 8 online tutorial translated to spanish
Oracle Java 8 online tutorial translated to spanish (work in progress) . Tutorial en linea de Oracle Java 8 traducido al español (trabajo en proceso) -
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Open Billiards is Open-Source multi-platform 2D billiards game, with game 8 ball, 8 ball and snooker.
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Grok-2.5
Large-scale xAI model for local inference with SGLang, Grok-2.5
...To use it, users must download over 500 GB of files and set them up locally with the SGLang inference engine. Grok-2.5 supports advanced inference with multi-GPU configurations, requiring at least 8 GPUs with more than 40 GB of memory each for optimal performance. It integrates with the SGLang framework to enable serving, testing, and chat-style interactions. The model comes with a post-training architecture and requires the correct chat template to function properly. It is released under the Grok 2 Community License Agreement, encouraging community experimentation and responsible use. -
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zen-moment
Minimalist meditation timer with breathing exercises and analytics
...Built with modern web technologies and optimized for performance across all devices, this application provides a clean, distraction-free environment for meditation practice. Key features include a precise meditation timer supporting 1-999 minute sessions with multiple presets, guided 4-7-8 breathing exercises based on Dr. Weil's proven relaxation technique, and an advanced analytics system that tracks practice patterns, habit consistency, and progress with achievement badges. The application also includes dark/light mode themes and 8 ambient background sound options for enhanced meditation experience. Built with Next.js 14, TypeScript, and Tailwind CSS, the application achieves Lighthouse scores above 95. ... -
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The Engine
Game creation engine with built-in BASIC interpreter.
...Interpreter and graphics engine run in parallel, in separate threads, and hence interpreter speed is not an issue. The interpreter is not chiefly designed for speed, but for comfortable development. The editor and command screen use a custom 8 x 8 font on a 64x16 character text display. There are currently three switchable screens: Game screen, Output/Command screen, and Editor screen. -
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Open System
Le Systéme d'exploitation multi-fonction.
Crée pour tout faire se systéme et multifonction: Jeux, Travail et divertisement -
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## What is Bitcuty(BCUTY), Bitcuty is Bitcuty, Bitcuty is ,,, BITCUTY_CODE_WEB = https://bitcuty-blockchain.sourceforge.io BITCUTY_CODE_GIT = https://github.com/bitcuty/bitcuty.git BITCUTY_CODE_GIT = https://github.com/Hashing-bProject/bitcuty.git BITCUTY_CODE_GIT = https://github.com/BLockChainsB/bitcuty.git BITCUTY_CODE_GIT = https://github.com/HB1teamProject/bitcuty.git BITCUTY_CRYPTONOTE_NAME = BITCUTY ,_ BITCUTY_CRYPTONOTE_SYMBOL = BCUTY ,_ BITCUTY_VALUE_DISPLAY_DECIMAL_POINT = 8 ,_ BITCUTY_BLOCK_GRANTED_FULL_REWARD_ZONE = 943718 ,_
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Titan Panel Classic
Titan Panel Classic for all World of Warcraft Classic versions
This version of Titan Panel is no longer being supported. Please migrate to the Titan Panel 8 version as soon as possible. -
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Based on WCS:Python, Classic, Fully Customizable, WarCraft:Source Mod written in Python, this is a Counter-Strike Source modification that implements the newbie friendly but challenging WC3 Frozen Throne game play and 8 races.
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Krea 2 Turbo
Fast 12B image model for high-quality text-to-image generation
...Built on a 12-billion-parameter Diffusion Transformer (DiT), it is a distilled and post-trained version of the Krea 2 Raw checkpoint, enabling photorealistic and artistic image synthesis in as few as eight inference steps. Designed for creative professionals, developers, and researchers, it supports concept art, design exploration, marketing assets, illustrations, and commercial visual production. Unlike the Raw checkpoint, which is intended for fine-tuning and LoRA training, Turbo is optimized for direct inference, delivering native resolutions up to 2K with excellent prompt adherence and broad aesthetic diversity. ... -
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Hy3 preview
Efficient MoE model for reasoning, coding, and AI agent workflows
...The model features 295B total parameters with only 21B activated during inference, plus a dedicated 3.8B Multi-Token Prediction (MTP) layer that accelerates generation through speculative decoding. Architecturally, it uses 192 routed experts with top-8 activation, a dense-MoE hybrid design, and a native 256K-token context window. Hy3-preview is optimized for efficient deployment while maintaining strong benchmark performance across reasoning, coding, and agent evaluations. It supports function calling, integration with popular agent frameworks such as OpenClaw and OpenCode, and deployment through Transformers. -
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Llama-3.2-1B
Llama 3.2–1B: Multilingual, instruction-tuned model for mobile AI
...It is part of the Llama 3.2 family, trained on up to 9 trillion tokens and aligned using supervised fine-tuning, preference optimization, and safety tuning. The model supports eight officially listed languages (including Spanish, German, Hindi, and Thai) but can be adapted to more. Llama 3.2-1B outperforms other open models in several benchmarks relative to its size and offers quantized versions for efficiency. It uses a refined transformer architecture with Grouped-Query Attention (GQA) and supports long context windows of up to 128k tokens. -
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Altar-1
Pruned GLM-5.3 model for self-hosted cybersecurity AI and coding
...Starting from GLM-5.3’s 753B-parameter Mixture-of-Experts architecture, Altar removes 34% of routed experts using REAP, leaving 168 of 256 experts per layer and approximately 504B parameters. Eight experts remain active per token, preserving roughly 40B active parameters during inference. The model was calibrated using cybersecurity traces, coding, tool calling, reasoning, English, and multilingual Wikipedia data to preserve domain specialists during pruning. Its routed experts use INT4 W4A16 AWQ quantization, while attention, shared experts, dense layers, and the output head remain BF16. ... -
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Solar Open 2
Efficient 250B MoE model for agents, coding, and long-context work
...The model supports a native 1M-token context window and uses NoPE instead of rotary positional encoding, reducing long-context KV-cache requirements. Solar Open 2 includes 321 experts, with eight routed experts plus one shared expert activated per token. It was pretrained on roughly 12 trillion tokens and supports English, Korean, and Japanese. Agent capabilities include multi-step reasoning, tool calling, MCP tools, and end-to-end task execution. It also offers direct-response and high-reasoning modes and supports deployment through Transformers, vLLM, SGLang, and quantized variants. -
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Llama-3.2-1B-Instruct
Instruction-tuned 1.2B LLM for multilingual text generation by Meta
...It builds upon the Llama 3.1 architecture and incorporates fine-tuning techniques like SFT, DPO, and quantization-aware training for improved alignment, efficiency, and safety. The model supports eight primary languages (including English, Spanish, Hindi, and Thai) and was trained on a curated mix of publicly available online data, with a December 2023 knowledge cutoff. Llama-3.2-1B is lightweight enough for deployment on constrained devices like smartphones, using formats like SpinQuant and QLoRA to reduce model size and latency. ... -
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LAN-Control is a plugin for the Linux-based Dreambox. It runs on all enigma1-based versions. The plugin allows to start servers via Wake-on-Lan. Up to 8 profiles can be stored. Furthermore, the servers-status (running/stopped) can be checked.
