Showing 2756 open source projects for "python-ldap"

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  • 1
    Style Aligned

    Style Aligned

    Official code for Style Aligned Image Generation via Shared Attention

    StyleAligned is a diffusion-model editing technique and codebase that preserves the visual “style” of an original image while applying new semantic edits driven by text. Instead of fully re-generating an image—and risking changes to lighting, texture, or rendering choices—the method aligns internal features across denoising steps so the target edit inherits the source style. This alignment acts like a constraint on the model’s evolution, steering composition, palette, and brushwork even as...
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  • 2
    DB-GPT-Hub

    DB-GPT-Hub

    A repository that contains models, datasets, and fine-tuning

    DB-GPT-Hub is an open-source repository that provides datasets, models, and training tools designed to improve large language models for database interaction tasks, particularly Text-to-SQL. The project serves as a specialized extension of the broader DB-GPT ecosystem, focusing on the preparation and evaluation of models capable of translating natural language questions into structured database queries. It offers a modular framework that supports data preparation, model fine-tuning,...
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  • 3
    DPM-Solver

    DPM-Solver

    Fast ODE Solver for Diffusion Probabilistic Model Sampling

    DPM-Solver is a machine learning research implementation focused on accelerating the sampling process in diffusion probabilistic models used for generative AI tasks. Diffusion models are powerful generative systems capable of producing high-quality images and other data, but traditional sampling methods often require hundreds or thousands of computational steps. The project introduces a specialized numerical solver designed to approximate the diffusion process using a small number of...
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  • 4
    YiVal

    YiVal

    Your Automatic Prompt Engineering Assistant for GenAI Applications

    YiVal is an open-source framework designed to automate prompt engineering and evaluation workflows for generative AI applications, enabling developers to systematically improve the performance of large language models. It focuses on experimentation and optimization by allowing users to test multiple prompt variations, configurations, and model parameters in parallel, then evaluate their outputs using structured metrics and scoring systems. The platform is particularly useful in production...
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  • 5
    TensorFlow Addons

    TensorFlow Addons

    Useful extra functionality for TensorFlow 2.x maintained by SIG-addons

    TensorFlow Addons is a repository of contributions that conform to well-established API patterns but implement new functionality not available in core TensorFlow. TensorFlow natively supports a large number of operators, layers, metrics, losses, and optimizers. However, in a fast-moving field like ML, there are many interesting new developments that cannot be integrated into core TensorFlow (because their broad applicability is not yet clear, or it is mostly used by a smaller subset of the...
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  • 6
    Adala

    Adala

    Adala: Autonomous DAta (Labeling) Agent framework

    Adala is a data-centric AI framework focused on dataset curation, annotation, and validation. It helps AI teams manage high-quality training datasets by providing tools for data auditing, error detection, and quality assessment.
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  • 7

    Telegram Logger

    Function that can be copy-pasted into any Python script to add logging

    This utility enables seamless message logging to a Telegram channel via a straightforward Curl command, leveraging Telegram bot capabilities. It's designed for developers needing a quick and efficient way to send updates or logs to a Telegram channel directly from their scripts or applications.
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  • 8

    Taylorplot_Neptune

    Creation of a Taylorplot for several machine learning models

    Here we present the lines of code for creating a taylor plot with python to display several machine learning models. We show the solution for displaying 10 models, but the list and number can be changed simply by modifying the sample list.
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  • 9
    pipeless

    pipeless

    A computer vision framework to create and deploy apps in minutes

    Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new...
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  • 10
    AI System & AI Infra

    AI System & AI Infra

    Tutorial repository focused on the full-stack design of AI systems

    AI System is an educational and technical tutorial repository focused on the full-stack design of artificial intelligence systems, covering the foundational infrastructure that powers modern deep learning workloads. The project explores the AI software and hardware stack end to end, including AI chips, AI compilers, inference engines, and training frameworks, helping learners understand how these components interact in real-world deployments. Rather than being a single library, it functions...
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  • 11
    EvaDB

    EvaDB

    Database system for building simpler and faster AI-powered application

    Over the last decade, AI models have radically changed the world of natural language processing and computer vision. They are accurate on various tasks ranging from question answering to object tracking in videos. To use an AI model, the user needs to program against multiple low-level libraries, like PyTorch, Hugging Face, Open AI, etc. This tedious process often leads to a complex AI app that glues together these libraries to accomplish the given task. This programming complexity prevents...
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  • 12
    Ellogon is a multi-lingual, cross-platform, general-purpose language engineering environment.
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  • 13
    OpenAssistant

    OpenAssistant

    Chat-based assistant that understands tasks

    OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so. In the same way that Stable Diffusion helped the world make art and images in new ways, we want to improve the world by providing amazing conversational AI. We are in the early stages of development, working from established research in applying RLHF to large language models. Open Assistant is a project organized by LAION and individuals around...
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  • 14
    XAgent

    XAgent

    An Autonomous LLM Agent for Complex Task Solving

    XAgent is an AI-driven autonomous agent framework capable of handling multi-step tasks across different domains. It enables AI agents to perform decision-making, task planning, and self-learning based on user-defined objectives, making it ideal for automation and research applications.
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  • 15
    ConsistencyDecoder

    ConsistencyDecoder

    Consistency Distilled Diff VAE

    ConsistencyDecoder is a Python package from OpenAI that introduces an improved decoding method for variational autoencoders (VAEs) used in Stable Diffusion pipelines. Instead of relying solely on the standard GAN or VAE decoder, this approach leverages a Consistency Distilled Diff VAE, designed to produce higher-quality and more stable outputs from encoded latents.
    Downloads: 4 This Week
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  • 16
    Langcorn

    Langcorn

    Serving LangChain LLM apps automagically with FastApi

    LangCorn is an API server that enables you to serve LangChain models and pipelines with ease, leveraging the power of FastAPI for a robust and efficient experience.
    Downloads: 0 This Week
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  • 17
    Shap-E

    Shap-E

    Generate 3D objects conditioned on text or images

    The shap-e repository provides the official code and model release for Shap-E, a conditional generative model designed to produce 3D assets (implicit functions, meshes, neural radiance fields) from text or image prompts. The model is built with a two-stage architecture: first an encoder that maps existing 3D assets into parameterizations of implicit functions, and then a conditional diffusion model trained on those parameterizations to generate new assets. Because it works at the level of...
    Downloads: 2 This Week
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  • 18
    customhys-qt
    This is the official repository for the CUSTOMHyS-Qt software. CUSTOMHyS-Qt is a GUI for the CUSTOMHyS framework, which is an interactive tool for customysing heuristic-based algorithms. The CUSTOMHyS-Qt is written in Python and uses the PyQt5 library for the GUI. Further references about the backend can be found in the CUSTOMHyS repository.
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  • 19
    Parallel WaveGAN

    Parallel WaveGAN

    Unofficial Parallel WaveGAN

    Parallel WaveGAN is an unofficial PyTorch implementation of several state-of-the-art non-autoregressive neural vocoders, centered on Parallel WaveGAN but also including MelGAN, Multiband-MelGAN, HiFi-GAN, and StyleMelGAN. Its main goal is to provide a real-time neural vocoder that can turn mel spectrograms into high-quality speech audio efficiently. The repository is designed to work hand-in-hand with ESPnet-TTS and NVIDIA Tacotron2-style front ends, so you can build complete TTS or singing...
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  • 20
    VALL-E X

    VALL-E X

    Open source implementation of Microsoft's VALL-E X zero-shot TTS model

    ...It also preserves aspects of the acoustic environment, such as background noise or reverb, making the generated audio feel more like it came from the same setting as the prompt. The repository includes Python APIs, sample scripts, ready-to-use voice presets, and demos hosted on Hugging Face Spaces and Google Colab so users can try it.
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  • 21
    AutoPR

    AutoPR

    Run AI-powered workflows over your codebase

    AutoPR is an AI-driven tool for automating pull request (PR) generation and review processes. It streamlines code contributions by suggesting fixes, generating pull requests, and reviewing code using AI models, reducing manual overhead for developers.
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  • 22
    NLG-Eval

    NLG-Eval

    Evaluation code for various unsupervised automated metrics

    NLG-Eval is a toolkit for evaluating the quality of natural language generation (NLG) outputs using multiple automated metrics such as BLEU, METEOR, and ROUGE.
    Downloads: 2 This Week
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  • 23
    TextGen

    TextGen

    textgen, Text Generation models

    Implementation of Text Generation models. textgen implements a variety of text generation models, including UDA, GPT2, Seq2Seq, BART, T5, SongNet and other models, out of the box. UDA, non-core word replacement. EDA, simple data augmentation technique: similar words, synonym replacement, random word insertion, deletion, replacement. This project refers to Google's UDA (non-core word replacement) algorithm and EDA algorithm, based on TF-IDF to replace some unimportant words in sentences with...
    Downloads: 1 This Week
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  • 24

    Liveliness and Face Identification

    Leading free and open-source liveliness check &face recognition system

    ...Essentially, it is an application that can be used as a standalone server or deployed in the cloud. You don’t need prior machine learning skills to set up and use. The application is customizable react based mobile friendly UI and Python based backend. The program is a real-time face detection application. It allows you to detect faces using your webcam and displays the video feed with oval drawn around the detected faces. When you run the program, a GUI window will appear. The window appears to do liveliness check and face detection. The description guides you to adjust the settings and click the "Start" button to begin face detection. ...
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  • 25
    CoTracker

    CoTracker

    CoTracker is a model for tracking any point (pixel) on a video

    CoTracker is a learning-based point tracking system that jointly follows many user-specified points across a video, rather than tracking each point independently. By reasoning about all tracks together, it can maintain temporal consistency, handle mutual occlusions, and reduce identity swaps when trajectories cross. The model takes sparse point queries on one frame and predicts their sub-pixel locations and a visibility score for every subsequent frame, producing long, coherent trajectories....
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