Search Results for "qt-eclipse-integration" - Page 24
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Showing 682 open source projects for "qt-eclipse-integration"
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LLM Applications
A comprehensive guide to building RAG-based LLM applications
LLM Applications is a practical reference repository that demonstrates how to build production-grade applications powered by large language models. The project focuses particularly on Retrieval-Augmented Generation architectures, which combine language models with external knowledge sources to improve accuracy and reliability. It provides step-by-step guidance for constructing systems that ingest documents, split them into chunks, generate embeddings, index them in vector databases, and... -
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Medusa
Framework for Accelerating LLM Generation with Multiple Decoding Heads
Medusa is a framework aimed at accelerating the generation capabilities of Large Language Models (LLMs) by employing multiple decoding heads. This approach allows for parallel processing during text generation, significantly enhancing throughput and reducing response times. Medusa is designed to be simple to implement and integrates with existing LLM infrastructures, making it a practical solution for scaling LLM applications. -
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fastquant
Backtest and optimize your ML trading strategies with only 3 lines
fastquant is a Python library designed to simplify quantitative financial analysis and algorithmic trading strategy development. The project focuses on making backtesting accessible by providing a high-level interface that allows users to test investment strategies with only a few lines of code. It integrates historical market data sources and trading frameworks so that users can quickly build experiments without constructing complex data pipelines. The framework enables users to test common... -
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macara
A converter for seamless transformation of files, data, and media ...
This application consolidates various scripts, including an AI feature (rembg), into a singular platform. The design of this software is evolutionary, allowing for the seamless integration of additional scripts, menus, or windows as needed. Serving as a versatile tool, it facilitates efficient file management, especially when handling a substantial volume of images, whether sorting by name or other attributes. These scripts are crafted to complement generative art AI technologies like Dall-e or stable diffusion. -
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AnyTrading
The most simple, flexible, and comprehensive OpenAI Gym trading
gym-anytrading is an OpenAI Gym-compatible environment designed for developing and testing reinforcement learning algorithms on trading strategies. It simulates trading environments for financial markets, including stocks and forex. -
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FastViT
This repository contains the official implementation of research
...The models use lightweight attention and carefully engineered blocks to minimize token mixing costs while preserving representation power. Training and inference recipes highlight straightforward integration into common vision tasks such as classification, detection, and segmentation. The codebase provides reference implementations and checkpoints that make it easy to evaluate or fine-tune on downstream datasets. In practice, FastViT offers drop-in backbones that reduce compute and memory pressure without exotic training tricks. -
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Promptify
se GPT or other prompt based models to get structured output
...This approach allows developers to perform tasks such as text classification, named entity recognition, question answering, and information extraction using consistent prompt templates. The library supports integration with multiple large language model providers, enabling users to experiment with various models without changing their overall workflow. -
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EasyRL
Reinforcement learning (RL) tutorial series
easy-rl is a beginner-friendly reinforcement learning (RL) tutorial series and framework developed by Datawhale China. It provides educational resources and implementations of various RL algorithms to help new researchers and practitioners learn RL concepts. -
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wukong-robot
Chinese voice dialogue robot/smart speaker project
wukong-robot is a Chinese voice assistant / smart speaker project built to let makers and hackers design highly customizable voice-controlled devices. It combines wake-word detection, automatic speech recognition, natural language understanding, and text-to-speech into a single framework aimed at the Chinese-speaking ecosystem. The project is positioned as a simple, flexible, and elegant platform that can run on devices like Raspberry Pi and other Linux-based boards, making it suitable for... -
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pyts
A Python package for time series classification
...It aims to make time series classification easily accessible by providing preprocessing and utility tools, and implementations of several time series classification algorithms. The package comes up with many unit tests and continuous integration ensures new code integration and backward compatibility. The package is distributed under the 3-clause BSD license. -
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learn2learn
A PyTorch Library for Meta-learning Research
Learn2Learn is a PyTorch-based library focused on meta-learning and few-shot learning research. It provides reusable components and meta-learning algorithms, making it easier to build, train, and evaluate models that can quickly adapt to new tasks with minimal data. Learn2Learn is widely used in research for tasks such as few-shot classification, reinforcement learning, and optimization. -
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TaskMatrix
Enable sending and receiving images during chatting
TaskMatrix is an experimental AI ecosystem designed to connect large language models with visual foundation models, APIs, and external systems in order to complete multimodal tasks collaboratively. The project expands beyond traditional chatbot behavior by enabling AI systems to process, generate, edit, and reason about images while coordinating multiple specialized models simultaneously. Originally introduced alongside the Visual ChatGPT concept, TaskMatrix acts as an orchestration... -
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PromethAI
Open-source framework that gives you AI Agents
PromethAI-Backend is a backend framework for AI-driven automation and knowledge extraction. It is designed to integrate with large language models (LLMs) to provide AI-enhanced workflows, including content generation, summarization, and data analysis. -
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RasaGPT
Headless Rasa chatbot platform with LLM integration and APIs
...It serves as a reference implementation and boilerplate for building conversational AI systems with retrieval and context injection. RasaGPT includes a FastAPI backend for creating custom bot endpoints, along with document ingestion and a training pipeline. It simplifies integration challenges between Rasa and LLM libraries, including metadata handling and library conflicts. RasaGPT supports multi-tenant deployments, session management, and custom schemas using pgvector. It also enables Telegram bot integration and remote access via ngrok. Docker support allows easier setup and deployment, particularly on macOS environments. ... -
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AI-powered enterprise search engine
AI-powered enterprise search engine
AI-powered enterprise search engine is an open-source, AI-powered enterprise search engine designed to help organizations quickly locate and retrieve information scattered across multiple internal tools, documents, and communication platforms. It enables users to search across sources such as Slack, Confluence, Jira, Google Drive, and other enterprise systems, consolidating fragmented knowledge into a single, unified search experience. By leveraging natural language processing, Gerev allows... -
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CORL
High-quality single-file implementations of SOTA Offline
CORL (Collection of Reinforcement Learning Environments for Control Tasks) is a modular and extensible set of high-quality reinforcement learning environments focused on continuous control and robotics. It aims to offer standardized environments suitable for benchmarking state-of-the-art RL algorithms in control tasks, including physics-based simulations and custom-designed scenarios. -
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ParlAI
A framework for training and evaluating AI models
ParlAI is a comprehensive research platform for building, training, and evaluating dialogue agents across a wide variety of tasks and datasets. It provides a unified interface—agents, teachers, and worlds—so the same model can be trained on multi-turn chit-chat, question answering, task-oriented dialogue, retrieval, or safety-focused datasets without changing core code. The library integrates tightly with PyTorch and supports both generative and retrieval-augmented models, along with... -
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TensorFlow Ranking
Learning to rank in TensorFlow
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform. Commonly used loss functions including pointwise, pairwise, and listwise losses. Commonly used ranking metrics like Mean Reciprocal Rank (MRR) and Normalized Discounted Cumulative Gain (NDCG). Multi-item (also known as groupwise) scoring functions. LambdaLoss implementation for direct ranking metric optimization. Unbiased Learning-to-Rank from biased feedback data. We envision that this library... -
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DiT (Diffusion Transformers)
Official PyTorch Implementation of "Scalable Diffusion Models"
...DiT achieves strong results on benchmarks like ImageNet and LSUN while being architecturally simple and highly modular. It supports variable resolution, conditioning on class or text embeddings, and integration with latent autoencoders (like those used in Stable Diffusion). -
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AnnLite
A fast embedded library for approximate nearest neighbor search
...The library uses a highly optimized approximate nearest neighbor search algorithm (HNSW) to search for nearest neighbors. The library allows you to search for nearest neighbors within a subset of the dataset. Smooth integration with neural search ecosystem including Jina and DocArray, so that users can easily expose search API with gRPC and/or HTTP. The library is easy to install and use. It is designed to be used with Python. To support search with filters, the annlite must be created with colums parameter, which is a series of fields you want to filter by. -
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Bot on Anything
Large model-based chatbot builder that can quickly integrate AI models
...Configuration is handled simply through a central JSON file where you define which model and which application channel you want to glue together, so developers can create sophisticated AI assistants without rewriting integration code from scratch. The architecture emphasizes reusability and extensibility, allowing the addition of new model backends or new channels with relative ease. It supports switching between multiple AI models and targets within the same project. -
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Transformers-Interpret
Model explainability that works seamlessly with Hugging Face
Transformers-Interpret is an interpretability tool for Transformer-based NLP models, providing insights into attention mechanisms and feature importance. -
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Img2Txt
Img2Txt - Extract Text From Images using AI
Important: If you are sharing this program. Please Include the official Download Link What is Img2Txt? Img2Txt is a Python-based application packaged using PyInstaller that utilizes the power of pytesseract, an AI-powered optical character recognition (OCR) library, to extract text from images and convert it into plain text. The application features a simple and modern user-friendly interface created using customtkinter, allowing users to easily process images and obtain the text... -
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PIFuHD
High-Resolution 3D Human Digitization from A Single Image
...The repo includes training pipelines, dataset loaders (for Multi-POP, etc.), and inference scripts for mesh output including depth maps for postprocessing. To help practical use, there are utilities for normal estimation, texture back-projection, mesh cleanup, and integration with rendering pipelines. -
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OptiMate
Libraries for optimizing AI models, inference speed, and GPU usage
Optimate is an open source collection of libraries designed to optimize the performance and cost efficiency of artificial intelligence models across different stages of the machine learning lifecycle. It groups several internal optimization tools developed by Nebuly AI into a single repository that focuses on improving inference speed, reducing infrastructure usage, and streamlining model training workflows. Its modules help developers automatically apply optimization techniques that better...