Showing 5 open source projects for "developer ide source"

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    RamaLama

    RamaLama

    Simplifies the local serving of AI models from any source

    RamaLama is an open-source developer tool that simplifies working with and serving AI models locally or in production by leveraging container technologies like Docker, Podman, and OCI registries, allowing AI inference workflows to be treated like standard container deployments. It abstracts away much of the complexity of configuring AI runtimes, dependencies, and hardware optimizations by detecting available GPUs (or falling back to CPU) and automatically pulling a container image pre-configured for the detected hardware environment. ...
    Downloads: 6 This Week
    Last Update:
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  • 2
    Xorbits Inference

    Xorbits Inference

    Replace OpenAI GPT with another LLM in your app

    ...Whether you are a researcher, developer, or data scientist, Xorbits Inference empowers you to unleash the full potential of cutting-edge AI models.
    Downloads: 6 This Week
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  • 3
    offyai

    offyai

    OffyAI — Local AI. Private by Design. Built for Your Machine.

    OffyAI is a modern local-first AI desktop application that brings a ChatGPT-like experience to your computer while keeping your AI workloads close to you. It is designed for users who want to run, manage, and interact with local Large Language Models (LLMs) through a clean desktop interface without depending entirely on cloud-based AI services.
    Downloads: 5 This Week
    Last Update:
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  • 4
    Sockeye

    Sockeye

    Sequence-to-sequence framework, focused on Neural Machine Translation

    Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. It implements distributed training and optimized inference for state-of-the-art models, powering Amazon Translate and other MT applications. For a quickstart guide to training a standard NMT model on any size of data, see the WMT 2014 English-German tutorial.
    Downloads: 0 This Week
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    BudgetML

    BudgetML

    Deploy a ML inference service on a budget in 10 lines of code

    Deploy a ML inference service on a budget in less than 10 lines of code. BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST,...
    Downloads: 0 This Week
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