Showing 6 open source projects for "python application template"

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  • Gen AI apps are built with MongoDB Atlas Icon
    Gen AI apps are built with MongoDB Atlas

    The database for AI-powered applications.

    MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
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    Auth for GenAI | Auth0

    Enable AI agents to securely access tools, workflows, and data with fine-grained control and just a few lines of code.

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  • 1
    DeepCamera

    DeepCamera

    Open-Source AI Camera. Empower any camera/CCTV

    DeepCamera empowers your traditional surveillance cameras and CCTV/NVR with machine learning technologies. It provides open-source facial recognition-based intrusion detection, fall detection, and parking lot monitoring with the inference engine on your local device. SharpAI-hub is the cloud hosting for AI applications that helps you deploy AI applications with your CCTV camera on your edge device in minutes. SharpAI yolov7_reid is an open-source Python application that leverages AI...
    Downloads: 2 This Week
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  • 2
    Triton Inference Server

    Triton Inference Server

    The Triton Inference Server provides an optimized cloud

    Triton Inference Server is an open-source inference serving software that streamlines AI inferencing. Triton enables teams to deploy any AI model from multiple deep learning and machine learning frameworks, including TensorRT, TensorFlow, PyTorch, ONNX, OpenVINO, Python, RAPIDS FIL, and more. Triton supports inference across cloud, data center, edge, and embedded devices on NVIDIA GPUs, x86 and ARM CPU, or AWS Inferentia. Triton delivers optimized performance for many query types, including...
    Downloads: 1 This Week
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  • 3
    Llama Recipes

    Llama Recipes

    Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT method

    The 'llama-recipes' repository is a companion to the Meta Llama models. We support the latest version, Llama 3.1, in this repository. The goal is to provide a scalable library for fine-tuning Meta Llama models, along with some example scripts and notebooks to quickly get started with using the models in a variety of use-cases, including fine-tuning for domain adaptation and building LLM-based applications with Llama and other tools in the LLM ecosystem. The examples here showcase how to run...
    Downloads: 0 This Week
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  • 4
    OpenVINO Training Extensions

    OpenVINO Training Extensions

    Trainable models and NN optimization tools

    OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference. When ote_cli is installed in the virtual environment, you can use the ote command line interface to perform various actions for templates related to the chosen task type, such as running, training, evaluating, exporting, etc. ote train trains a model (a particular model template) on a dataset and saves results in two files. ote...
    Downloads: 0 This Week
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    Comprehensive Cybersecurity to Safeguard Your Organization | SOCRadar

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  • 5
    DoWhy

    DoWhy

    DoWhy is a Python library for causal inference

    DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks. Much like machine learning libraries have done for prediction, DoWhy is a Python library that aims to spark causal thinking and analysis. DoWhy provides a wide variety of algorithms for effect estimation, causal structure learning, diagnosis of causal...
    Downloads: 0 This Week
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  • 6
    TensorFlow Model Optimization Toolkit

    TensorFlow Model Optimization Toolkit

    A toolkit to optimize ML models for deployment for Keras & TensorFlow

    ... and optimization tool depending on your task. In many cases, pre-optimized models can improve the efficiency of your application. Try the post-training tools to optimize an already-trained TensorFlow model. Use training-time optimization tools and learn about the techniques.
    Downloads: 0 This Week
    Last Update:
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