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  1. README.md

    MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.
    
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  2. docs/de/docs/deployment/concepts.md

    ### Serverspeicher
    
    Wenn Ihr Code beispielsweise ein Machine-Learning-Modell mit **1 GB Größe** lädt und Sie einen Prozess mit Ihrer API ausführen, verbraucht dieser mindestens 1 GB RAM. Und wenn Sie **4 Prozesse** (4 Worker) starten, verbraucht jeder 1 GB RAM. Insgesamt verbraucht Ihre API also **4 GB RAM**.
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  3. docs/tr/docs/index.md

    ## Görüşler
    
    "_[...] Bugünlerde **FastAPI**'ı çok fazla kullanıyorum. [...] Aslında bunu ekibimin **Microsoft'taki Machine Learning servislerinin** tamamında kullanmayı planlıyorum. Bunlardan bazıları **Windows**'un ana ürünlerine ve **Office** ürünlerine entegre ediliyor._"
    
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  4. docs/pt/docs/index.md

    ## Opiniões
    
    "*[...] Estou usando **FastAPI** muito esses dias. [...] Estou na verdade planejando utilizar ele em todos os times de **serviços _Machine Learning_ na Microsoft**. Alguns deles estão sendo integrados no _core_ do produto **Windows** e alguns produtos **Office**.*"
    
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  5. tensorflow/c/BUILD

    # Tests
    
    tf_cuda_library(
        name = "c_test_util",
        testonly = 1,
        srcs = ["c_test_util.cc"],
        hdrs = ["c_test_util.h"],
        visibility = [
            "//learning/brain:__subpackages__",
            "//tensorflow:__subpackages__",
        ],
        deps = [
            ":c_api",
            ":c_api_experimental",
            "//tensorflow/core:lib",
            "//tensorflow/core:protos_all_cc",
    Plain Text
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  6. RELEASE.md

            optimizer.
        *   **Learning rate schedule access.** When using a `LearningRateSchedule`,
            The new optimizer's `learning_rate` property returns the
            current learning rate value instead of a `LearningRateSchedule` object
            as before. If you need to access the `LearningRateSchedule` object,
            please use `optimizer._learning_rate`.
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  7. tensorflow/c/eager/BUILD

        ],
    )
    
    tf_cuda_library(
        name = "c_api_test_util",
        testonly = 1,
        srcs = ["c_api_test_util.cc"],
        hdrs = ["c_api_test_util.h"],
        visibility = [
            "//learning/brain:__subpackages__",
            "//tensorflow:__subpackages__",
        ],
        deps = [
            ":c_api",
            ":c_api_experimental",
            ":c_api_internal",
            "//tensorflow/c:c_test_util",
    Plain Text
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  8. helm-releases/minio-5.0.15.tgz

    inio/blob/master/LICENSE) MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads. | IMPORTANT | | ---------- | | This Helm chart is community built, maintained, and supported. MinIO does not guarantee support for any given bug, feature request, or update referencing this chart. <br/><br/>...
    Others
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  9. helm-releases/minio-5.1.0.tgz

    inio/blob/master/LICENSE) MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads. | IMPORTANT | | ---------- | | This Helm chart is community built, maintained, and supported. MinIO does not guarantee support for any given bug, feature request, or update referencing this chart. <br/><br/>...
    Others
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  10. cmd/testdata/xl-meta-merge.zip

    ze=true)](https://min.io) MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads. This README provides quickstart instructions on running MinIO on bare metal hardware, including container-based installations. For Kubernetes environments, use the [MinIO Kubernetes Operator](https://gi...
    ZIP Archive
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