Showing 10 open source projects for "full stack framework"

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  • Dragonfly | An In-Memory Data Store without Limits Icon
    Dragonfly | An In-Memory Data Store without Limits

    Dragonfly Cloud is engineered to handle the heaviest data workloads with the strictest security requirements.

    Dragonfly is a drop-in Redis replacement that is designed for heavy data workloads running on modern cloud hardware. Migrate in less than a day and experience up to 25X the performance on half the infrastructure.
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  • Your go-to FinOps platform Icon
    Your go-to FinOps platform

    Analyze, optimize, and govern your multi-cloud environment effortlessly with AI Agentic FinOps.

    Unlike reporting-only FinOps tools, FinOpsly unifies cloud (AWS, Azure, GCP), data (Snowflake, Databricks, BigQuery), and AI costs into a single system of action — enabling teams to plan spend before it happens, automate optimization safely, and prove value in weeks, not quarters.
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  • 1
    tvm

    tvm

    Open deep learning compiler stack for cpu, gpu, etc.

    Apache TVM is an open source machine learning compiler framework for CPUs, GPUs, and machine learning accelerators. It aims to enable machine learning engineers to optimize and run computations efficiently on any hardware backend. The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging...
    Downloads: 1 This Week
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  • 2
    PaddleX

    PaddleX

    PaddlePaddle End-to-End Development Toolkit

    PaddleX is a deep learning full-process development tool based on the core framework, development kit, and tool components of Paddle. It has three characteristics opening up the whole process, integrating industrial practice, and being easy to use and integrate. Image classification and labeling is the most basic and simplest labeling task. Users only need to put pictures belonging to the same category in the same folder.
    Downloads: 2 This Week
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  • 3
    PyTorch Geometric Temporal

    PyTorch Geometric Temporal

    Spatiotemporal Signal Processing with Neural Machine Learning Models

    ...PyTorch Geometric Temporal makes implementing Dynamic and Temporal Graph Neural Networks quite easy - see the accompanying tutorial. Head over to our documentation to find out more about installation, creation of datasets and a full list of implemented methods and available datasets.
    Downloads: 0 This Week
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  • 4
    Lightly

    Lightly

    A python library for self-supervised learning on images

    A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training...
    Downloads: 0 This Week
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  • Create stunning, professional email signatures in minutes Icon
    Create stunning, professional email signatures in minutes

    For companies looking to create, assign and manage all their employees email signatures and add targeted marketing banners.

    Create, assign and manage all your employees’ email signatures and add targeted marketing banners. Stop getting worked up about your signatures! Leverage a centralized interface to easily create and manage the email signatures of all your employees. Take advantage of each email to broadcast and amplify your brand. Letsignit helps you regain control over your digital identity. Harmonize 100% of your employee’s email signatures in just a few clicks! 121 professional emails are received and 40 are sent every day by an employee. With Letsignit, turn every email into a powerful communication opportunity: send the right message to the right person at the right time! Innovative more than tech, inspiring more than following. Authentic more than overrated, close more than "think big", trustworthy more than doubtful. Hands-on more than complex, available but yet premium, fun but yet expert.
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  • 5
    Jina

    Jina

    Build cross-modal and multimodal applications on the cloud

    Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP,...
    Downloads: 0 This Week
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  • 6
    Lightning-Hydra-Template

    Lightning-Hydra-Template

    PyTorch Lightning + Hydra. A very user-friendly template

    ...PyTorch Lightning, a lightweight PyTorch wrapper for high-performance AI research. Think of it as a framework for organizing your PyTorch code. Hydra, a framework for elegantly configuring complex applications. The key feature is the ability to dynamically create a hierarchical configuration by composition and override it through config files and the command line.
    Downloads: 0 This Week
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  • 7
    Deep learning time series forecasting

    Deep learning time series forecasting

    Deep learning PyTorch library for time series forecasting

    Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series forecasting framework. ...
    Downloads: 0 This Week
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  • 8
    Catalyst

    Catalyst

    Accelerated deep learning R&D

    Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. ...
    Downloads: 1 This Week
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  • 9
    End-to-End Negotiator

    End-to-End Negotiator

    Deal or No Deal? End-to-End Learning for Negotiation Dialogues

    End-to-End Negotiator is a PyTorch-based research framework developed by Facebook AI Research to train neural agents capable of conducting strategic negotiations in natural language. The project implements the models presented in two key papers: “Deal or No Deal? End-to-End Learning for Negotiation Dialogues” and “Hierarchical Text Generation and Planning for Strategic Dialogue”. It enables agents to plan, reason, and communicate effectively to maximize outcomes in multi-turn negotiations...
    Downloads: 0 This Week
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  • Diagnose and Resolve IT Issues in Real Time Icon
    Diagnose and Resolve IT Issues in Real Time

    Engage your employees and agents more efficiently with ScreenMeet as a seamless extension of your existing IT Service Delivery Platform.

    ScreenMeet’s unique combination of video calling, screen share, and remote desktop functionality lets you quickly diagnose hardware and software issues with no frustration.
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  • 10
    jieba

    jieba

    Stuttering Chinese word segmentation

    "Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable for word segmentation in search engines. The paddle mode uses the PaddlePaddle deep learning framework to train the sequence labeling (bidirectional GRU) network model to achieve word segmentation. ...
    Downloads: 1 This Week
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