Search Results for "transfer function model" - Page 13
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Showing 339 open source projects for "transfer function model"
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Breeze a multiple class model neural network development system. Network models include multi-threaded Backpropagation and Radial Basis Function Networks, for time series prediction.
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This software can simulate heat transfer in solid heterogenous materia using cellular automata. There are two different simulation methods and several test model implemented at the moment. It is also possible to define boundary conditions.
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Volcast is a small, flexible and fast volume raycaster. Raycasting is done entirely on the GPU (nv6800+). The featureset includes: pre-integration, real-time editing of transfer-function and support for 8/16Bit volumes.
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DOMAPI is a set of library routines for the 'C' programming language implementing the W3C Document Object Model. Function signatures match Oracle's XML Developer Kit so DOMAPI will be source-code compatible with Oracle's XDK.
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Robust personal accounting with function of double entry booking, e-billing, tax processing, budgeting, and foreign currency ex rate revaluation. Multi-language is supported. Pl enjoy encrypted p2p invoice transfer and info-on-finger style user interface
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An easy-to-use, multifunctional graphical FTP client with FXP-support (to come), based on the model of FlashFXP for Windows.
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elspy is an extension to the Exim MTA that allows Exim users to supply a local_scan() function written in Python instead of C. (Exim's local_scan() API lets sysadmins supply site-specific code for approving/rejecting email messages at SMTP time.)
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PHP-IRC is a PHP 5 based IRC bot which employs several features such as dcc chat administration, dcc file transfer support, user-defined function modules/scripting, custom chat handlers, MySQL database support, user-tracking, and more.
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This application allows you to get any digital images uploaded to the Internet as quickly as possible. This includes an image scaling and rotating function and an ftp function.
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dtoGen is a java source generation tool that can ease the development of multi-tier systems by offering a reliable solution to obtain the data transfer objects out of the domain model objects without hand-writting additional code.
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Skyfire is a GUI client for the Peer Distributed Transfer Protocol (PDTP). PDTP provides BitTorrent-like download swarming with an HTTP/FTP-like client/server model. Skyfire is written in C and C++ using Qt and builds on Windows and POSIX platforms.
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Tattoo will provide a set of command-line scripts for analyzing raw tcpdump files or ASCII hexadecimal representations of network traffic to identify format, function, and communication model.
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This project will provide a suite of applications which will function as a remote file download accelerator . The roadmap for the project is 1. proof of concept (Command Line Interface) cli client. 2. resume / failure recovery added to
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Ministral 3 3B Reasoning 2512
Compact 3B-param multimodal model for efficient on-device reasoning
...Despite its modest size, the model is designed for edge deployment and can run locally, fitting in ~16 GB of VRAM in BF16 or under 8 GB of RAM/VRAM when quantized. It supports dozens of languages, allowing it to function across global and multilingual contexts. The model retains strong system-prompt adherence, supports function-calling with structured JSON output, and offers a large 256k token context window for extended context reasoning. -
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Ministral 3 8B Instruct 2512
Compact 8B multimodal instruct model optimized for edge deployment
...Designed for edge deployment, the model can run on a wide range of hardware and fits locally on a single 12GB GPU, with the option for even smaller quantized configurations. Its multilingual support covers dozens of major languages, allowing it to work across diverse global environments and applications. The model adheres reliably to system prompts, supports native function calling, and outputs clean JSON, giving it strong tool-use behavior. -
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Hy3 preview
Efficient MoE model for reasoning, coding, and AI agent workflows
Hy3 preview is Tencent Hunyuan’s latest open-weight Mixture-of-Experts language model, designed for advanced reasoning, coding, instruction following, and autonomous agent workflows. It is the first model built on Tencent’s rebuilt training infrastructure and introduces significant improvements in context learning, software engineering, and tool-based task execution. 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. ... -
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t5-base
Flexible text-to-text transformer model for multilingual NLP tasks
...It was trained on the C4 dataset, along with a variety of supervised NLP benchmarks, using both unsupervised denoising and supervised objectives. The model supports multiple languages, including English, French, Romanian, and German. Its flexible architecture and consistent input/output format simplify model reuse and transfer learning across different NLP tasks. T5-base achieves competitive performance across 24 language understanding tasks, as documented in its research paper. -
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Ministral 3 8B Reasoning 2512
Efficient 8B multimodal model tuned for advanced reasoning tasks.
...Despite its reasoning-focused training, the model remains edge-optimized and can run locally on a single 24GB GPU in BF16, or under 12GB when quantized. It supports dozens of languages, adheres reliably to system prompts, and provides native function calling and structured JSON output—key capabilities for agentic and automation workflows. The model also includes a 256k context window, allowing it to handle long documents and extended reasoning chains. -
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Ministral 3 14B Reasoning 2512
High-precision 14B multimodal model built for advanced reasoning tasks
...Despite its scale, the model is engineered for practical deployment and can run locally on 32GB of VRAM in BF16 or under 24GB when quantized. It maintains robust system-prompt adherence, supports dozens of languages, and provides native function calling with clean JSON output for agentic workflows. The model's architecture also delivers a 256k context window, unlocking large-document analysis and long-form reasoning. -
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Ministral 3 3B Instruct 2512
Ultra-efficient 3B multimodal instruct model built for edge deployment
...Despite its small size, it delivers efficient real-time performance and can run locally on a single 8GB GPU, with further memory reductions through quantization. It supports dozens of languages across major global regions, making it well-suited for multilingual and embedded applications. The model also provides function calling, clean JSON output, and stable tool-use behavior, enabling it to serve as a small but effective agentic system. -
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DiffusionGemma
NVFP4 DiffusionGemma model for fast multimodal text generation
...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. 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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Gemma 4 12B
Unified multimodal Gemma model for local coding and reasoning
...It supports text, image, audio, and video inputs with text output, making it useful for transcription, image understanding, video analysis, coding, and agentic workflows. The model has 11.95B parameters, 48 layers, a 256K-token context window, and support for over 140 languages. It also includes configurable thinking modes, native system prompt support, function calling, and strong benchmark performance for its size. It is optimized for consumer GPUs, workstations, and streamlined local deployment. -
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Gemma 4
Google’s flagship dense multimodal model for coding and reasoning
...Gemma 4 31B supports native function calling, structured outputs, and more than 140 languages, making it suitable for enterprise assistants, coding agents, document analysis, and multilingual applications. Google positions it as a frontier-level model that can run on consumer GPUs and workstations while achieving leading results across reasoning, mathematics, coding, and multimodal benchmarks. -
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Hermes 4
Hermes 4 FP8: hybrid reasoning Llama-3.1-405B model by Nous Research
...The model is designed for schema adherence, producing valid JSON and repairing malformed outputs, making it highly suitable for tool use and function calling. Hermes 4 is engineered for superior steerability with reduced refusal rates, aligning responses to user values while preserving assistant quality. It achieves state-of-the-art results on RefusalBench, outperforming both closed and open models in balancing helpfulness with adaptability.
