Showing 5 open source projects for "arm-aonly"

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  • Fully Managed MySQL, PostgreSQL, and SQL Server Icon
    Fully Managed MySQL, PostgreSQL, and SQL Server

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    Forever Free Full-Stack Observability | Grafana Cloud

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  • 1
    Cactus

    Cactus

    Low-latency AI inference engine optimized for mobile devices

    Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing large models to run within the constraints of mobile hardware. It supports a wide range of AI tasks including text generation, speech-to-text, vision processing, and retrieval-augmented workflows through a unified API interface. ...
    Downloads: 0 This Week
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  • 2
    Triton Inference Server

    Triton Inference Server

    The Triton Inference Server provides an optimized cloud

    ...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 real-time, batched, ensembles, and audio/video streaming. Provides Backend API that allows adding custom backends and pre/post-processing operations. Model pipelines using Ensembling or Business Logic Scripting (BLS). HTTP/REST and GRPC inference protocols based on the community-developed KServe protocol. ...
    Downloads: 3 This Week
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  • 3
    Meta-World

    Meta-World

    Collections of robotics environments

    Meta-World is an open-source benchmark suite of robotic manipulation environments focused on multi-task and meta reinforcement learning. It provides a large collection of continuous-control tasks, such as reaching, pushing, opening doors, and manipulating objects with a simulated robot arm. The library defines standardized benchmarks like MT1, MT10, and MT50 for multi-task learning, where a single policy is trained across different numbers of tasks. It also offers meta-learning benchmarks (ML1, ML10, ML45) that evaluate few-shot adaptation to new goals or entirely new tasks. The environments adhere to the Gymnasium API, which makes them easy to plug into existing RL pipelines, and they support both synchronous and asynchronous vectorized execution for running many environments in parallel. ...
    Downloads: 0 This Week
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  • 4
    Fractal Neuro Oscillator

    Fractal Neuro Oscillator

    A fractal neural network

    The Fractal Neuro Oscillator is a neural network made up of threshold logic elements connected in a fractal manner. In a conventional network, information enters at the synapses and neurons fire or not. With a Fractal Neuro Oscillator, the synapse connections are randomized and information enters by firing neurons and then measuring the percentage of time firing of select neurons to generate an output value. These oscillation states can be summarized into a digest pattern to...
    Downloads: 9 This Week
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  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

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  • 5
    NanoDet-Plus

    NanoDet-Plus

    Lightweight anchor-free object detection model

    Super fast and high accuracy lightweight anchor-free object detection model. Real-time on mobile devices. NanoDet is a FCOS-style one-stage anchor-free object detection model which using Generalized Focal Loss as classification and regression loss. In NanoDet-Plus, we propose a novel label assignment strategy with a simple assign guidance module (AGM) and a dynamic soft label assigner (DSLA) to solve the optimal label assignment problem in lightweight model training. We also introduce a...
    Downloads: 8 This Week
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