Search Results for "scada open source" - Page 7
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Showing 405 open source projects for "scada open source"
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MegaParse
File Parser optimised for LLM Ingestion with no loss
MegaParse is a file parser optimized for Large Language Model (LLM) ingestion, ensuring no loss of information. It efficiently parses various document formats, such as PDFs, DOCX, and PPTX, converting them into formats ideal for processing by LLMs. This tool is essential for applications that require accurate and comprehensive data extraction from diverse document types. -
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HumanEval
Code for the paper "Evaluating Large Language Models Trained on Code"
human-eval is a benchmark dataset and evaluation framework created by OpenAI for measuring the ability of language models to generate correct code. It consists of hand-written programming problems with unit tests, designed to assess functional correctness rather than superficial metrics like text similarity. Each task includes a natural language prompt and a function signature, requiring the model to generate an implementation that passes all provided tests. The benchmark has become a... -
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Mosec
A high-performance ML model serving framework, offers dynamic batching
Mosec is a high-performance and flexible model-serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. -
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Gemini Fullstack LangGraph Quickstart
Get started w/ building Fullstack Agents using Gemini 2.5 & LangGraph
gemini-fullstack-langgraph-quickstart is a fullstack reference application from Google DeepMind’s Gemini team that demonstrates how to build a research-augmented conversational AI system using LangGraph and Google Gemini models. The project features a React (Vite) frontend and a LangGraph/FastAPI backend designed to work together seamlessly for real-time research and reasoning tasks. The backend agent dynamically generates search queries based on user input, retrieves information via the... -
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SAG
SQL-Driven RAG Engine
SAG is an open-source SQL-driven retrieval-augmented generation engine that dynamically constructs knowledge graphs during query processing. Instead of relying on a static knowledge graph prepared in advance, the system automatically builds relational structures between entities while processing user queries. Documents are first decomposed into atomic semantic events, which are then represented using multidimensional natural language vectors. -
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AIDE ML
AI-Driven Exploration in the Space of Code
AIDE ML is an open-source research framework designed to explore automated machine learning development through agent-based search and code optimization. The project implements the AIDE algorithm, which uses a tree-search strategy guided by large language models to iteratively generate, evaluate, and refine code. Instead of relying on manual experimentation, the agent autonomously drafts machine learning pipelines, debugs errors, and benchmarks performance against user-defined evaluation metrics. ... -
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Claude Code Skills & Plugins Hub
270+ Claude Code plugins with 739 agent skills
Claude Code Plugins Plus Skills is a large open-source ecosystem of plugins and AI “skills” designed to extend the capabilities of Claude Code development agents. The repository functions as a marketplace-style collection of hundreds of plugins and specialized skills that enable Claude Code to perform complex development, automation, and operational tasks. These plugins cover a wide range of domains including DevOps automation, security testing, API debugging, infrastructure management, and AI workflow orchestration. ... -
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Synthetic Data Generator
SDG is a specialized framework
Synthetic Data Generator is an open-source framework designed to generate high-quality synthetic tabular datasets that replicate the statistical characteristics of real data while avoiding privacy risks. The platform enables developers and data scientists to create artificial datasets that preserve important relationships between variables without containing sensitive personal information. -
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LLM Workflow Engine
Power CLI and Workflow manager for LLMs (core package)
LLM Workflow Engine is an open-source command-line framework designed to integrate large language models into automated workflows and developer environments. The platform allows users to interact with AI models directly from the terminal, enabling conversational AI access through shell commands and scripts. Instead of focusing solely on chat interactions, the system is built to embed LLM calls into larger automation pipelines where model outputs can drive decision making or trigger additional processes. ... -
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AI Engineering Hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications
The AI Engineering Hub repository is a large open-source collection of hands-on projects, tutorials, and real-world AI engineering resources designed to help developers learn and build with modern AI technologies, especially large language models (LLMs), retrieval-augmented generation (RAG), and agent-based systems. It includes more than 90 production-ready projects across skill levels, organized into beginner, intermediate, and advanced categories to guide users progressively from simple experiments to complex AI workflows. ... -
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LLM Colosseum
Benchmark LLMs by fighting in Street Fighter 3
LLM-Colosseum is an experimental benchmarking framework designed to evaluate the capabilities of large language models through gameplay interactions rather than traditional text-based benchmarks. The system places language models inside the environment of the classic video game Street Fighter III, where they must interpret the game state and decide which actions to perform during combat. This setup creates a dynamic environment that tests reasoning, situational awareness, and decision-making... -
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RAPTOR
The official implementation of RAPTOR
RAPTOR is a retrieval architecture designed to improve retrieval-augmented generation systems by organizing documents into hierarchical structures that enable more effective context retrieval. Traditional RAG systems typically retrieve small text chunks independently, which can limit a model’s ability to understand broader document context. RAPTOR addresses this limitation by recursively embedding, clustering, and summarizing documents to create a tree-structured hierarchy of information.... -
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GLM-V
GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning
GLM-V is an open-source vision-language model (VLM) series from ZhipuAI that extends the GLM foundation models into multimodal reasoning and perception. The repository provides both GLM-4.5V and GLM-4.1V models, designed to advance beyond basic perception toward higher-level reasoning, long-context understanding, and agent-based applications. GLM-4.5V builds on the flagship GLM-4.5-Air foundation (106B parameters, 12B active), achieving state-of-the-art results on 42 benchmarks across image, video, document, GUI, and grounding tasks. ... -
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Qwen2.5-Math
A series of math-specific large language models of our Qwen2 series
...Unlike its predecessor Qwen2-Math, Qwen2.5-Math supports both Chain-of-Thought (CoT) reasoning and Tool-Integrated Reasoning (TIR) for solving math problems, and works in both Chinese and English. It is optimized for solving mathematical benchmarks and exams; the 72B-Instruct model achieves state-of-the-art results among open source models on many English and Chinese math tasks. -
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SkillOpt
Text-space optimizer that trains reusable natural-language skills
SkillOpt is a Microsoft research project for improving frozen LLM agents by optimizing reusable natural-language skill documents. Instead of changing model weights, it treats a compact skill file as the trainable state of the agent. The system learns from agent rollouts, reflection, bounded edits, and validation gates to produce better instructions over time. Its output is a deployable best_skill.md artifact that can be reused across agent tasks. The project is focused on making agents more... -
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RLHF-Reward-Modeling
Recipes to train reward model for RLHF
...It supports multiple optimization strategies commonly used in alignment pipelines, including reinforcement learning with PPO, iterative supervised fine-tuning using rejection sampling, and direct preference optimization methods. The project also includes evaluation results showing that the trained reward models can achieve competitive performance compared with other open-source alignment systems. -
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Awesome LLM Apps
Collection of awesome LLM apps with AI Agents and RAG using OpenAI
Awesome LLM Apps is a community-curated directory of interesting, practical, and innovative applications built on or around large language models, serving as a discovery hub for developers, researchers, and enthusiasts. The list spans a wide range of categories including productivity tools, creative assistants, utilities, education platforms, research frameworks, and niche vertical apps, showcasing how generative models are being used across domains. Each entry includes a brief description,... -
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OpenCompass
OpenCompass is an LLM evaluation platform
Just like a compass guides us on our journey, OpenCompass will guide you through the complex landscape of evaluating large language models. With its powerful algorithms and intuitive interface, OpenCompass makes it easy to assess the quality and effectiveness of your NLP models. OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Pre-support for 20+ HuggingFace and API models, a model evaluation... -
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Qwen3-Omni
Qwen3-omni is a natively end-to-end, omni-modal LLM
...The model supports 119 text languages, 19 speech input languages, and 10 speech output languages. It achieves state-of-the-art results: across 36 audio and audio-visual benchmarks, it hits open-source SOTA on 32 and overall SOTA on 22, outperforming or matching strong closed-source models such as Gemini-2.5 Pro and GPT-4o. To reduce latency, especially in audio/video streaming, Talker predicts discrete speech codecs via a multi-codebook scheme and replaces heavier diffusion approaches. -
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Coconut
Training Large Language Model to Reason in a Continuous Latent Space
Coconut is the official PyTorch implementation of the research paper “Training Large Language Models to Reason in a Continuous Latent Space.” The framework introduces a novel method for enhancing large language models (LLMs) with continuous latent reasoning steps, enabling them to generate and refine reasoning chains within a learned latent space rather than relying solely on discrete symbolic reasoning. It supports training across multiple reasoning paradigms—including standard... -
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BertViz
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
BertViz is an interactive tool for visualizing attention in Transformer language models such as BERT, GPT2, or T5. It can be run inside a Jupyter or Colab notebook through a simple Python API that supports most Huggingface models. BertViz extends the Tensor2Tensor visualization tool by Llion Jones, providing multiple views that each offer a unique lens into the attention mechanism. The head view visualizes attention for one or more attention heads in the same layer. It is based on the... -
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mergekit
Tools for merging pretrained large language models
mergekit is an open-source toolkit designed to combine multiple pretrained language models into a single unified model through parameter merging techniques. The framework enables developers to merge model checkpoints so that the resulting model inherits capabilities from several source models without requiring additional training. This approach allows researchers to combine specialized models into a more versatile system capable of performing multiple tasks. mergekit implements a variety of merging algorithms and strategies that control how model parameters are blended together during the merging process. ... -
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bert4torch
An elegent pytorch implement of transformers
An elegant PyTorch implement of transformers. -
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yt-fts
Search all of YouTube from the command line
yt-fts, short for YouTube Full Text Search, is an open-source command-line tool that enables users to search the spoken content of YouTube videos by indexing their subtitles. The program automatically downloads subtitles from a specified YouTube channel using the yt-dlp utility and stores them in a local SQLite database. Once indexed, users can perform full-text searches across all transcripts to quickly locate keywords or phrases mentioned within the videos. -
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Xtuner
A Next-Generation Training Engine Built for Ultra-Large MoE Models
Xtuner is a large-scale training engine designed for efficient training and fine-tuning of modern large language models, particularly mixture-of-experts architectures. The framework focuses on enabling scalable training for extremely large models while maintaining efficiency across distributed computing environments. Unlike traditional 3D parallel training strategies, XTuner introduces optimized parallelism techniques that simplify scaling and reduce system complexity when training massive...
