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  1. docs/en/docs/deployment/concepts.md

    ### Server Memory
    
    For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**.
    
    And if your remote server or virtual machine only has 3 GB of RAM, trying to load more than 4 GB of RAM will cause problems. 🚨
    
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  2. api/go1.11.txt

    pkg debug/elf, const EM_C166 = 116
    pkg debug/elf, const EM_C166 Machine
    pkg debug/elf, const EM_CDP = 215
    pkg debug/elf, const EM_CDP Machine
    pkg debug/elf, const EM_CE = 119
    pkg debug/elf, const EM_CE Machine
    pkg debug/elf, const EM_CLOUDSHIELD = 192
    pkg debug/elf, const EM_CLOUDSHIELD Machine
    pkg debug/elf, const EM_COGE = 216
    pkg debug/elf, const EM_COGE Machine
    pkg debug/elf, const EM_COOL = 217
    pkg debug/elf, const EM_COOL Machine
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  3. docs/pt/docs/advanced/events.md

    ## Caso de uso
    
    Vamos iniciar com um exemplo de **caso de uso** e então ver como resolvê-lo com isso.
    
    Vamos imaginar que você tem alguns **modelos de _machine learning_** que deseja usar para lidar com as requisições. 🤖
    
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  4. common-protos/k8s.io/api/events/v1beta1/generated.proto

      // This field cannot be empty for new Events and it can have at most 128 characters.
      // +optional
      optional string reportingInstance = 5;
    
      // action is what action was taken/failed regarding to the regarding object. It is machine-readable.
      // This field can have at most 128 characters.
      // +optional
      optional string action = 6;
    
      // reason is why the action was taken. It is human-readable.
      // This field can have at most 128 characters.
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  5. docs/pt/docs/async.md

    * **Machine Learning**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande folha de papel com números e multiplicando todos eles juntos e ao mesmo tempo.
    
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  6. docs/fr/docs/async.md

    * L'apprentissage automatique (ou **Machine Learning**) : cela nécessite de nombreuses multiplications de matrices et vecteurs. Imaginez une énorme feuille de calcul remplie de nombres que vous multiplierez entre eux tous au même moment.
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  7. docs/fr/docs/deployment/manually.md

    Lorsqu'on se réfère à la machine distante, il est courant de l'appeler **serveur**, mais aussi **machine**, **VM** (machine virtuelle), **nœud**. Tout cela fait référence à un type de machine distante, exécutant  Linux, en règle générale, sur laquelle vous exécutez des programmes.
    
    
    ## Installer le programme serveur
    
    Vous pouvez installer un serveur compatible ASGI avec :
    
    === "Uvicorn"
    
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  8. docs/en/docs/deployment/manually.md

    When referring to the remote machine, it's common to call it **server**, but also **machine**, **VM** (virtual machine), **node**. Those all refer to some type of remote machine, normally running Linux, where you run programs.
    
    ## Install the Server Program
    
    You can install an ASGI compatible server with:
    
    === "Uvicorn"
    
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  9. docs/en/docs/deployment/https.md

        * The contents are **encrypted**, even though they are being sent with the **HTTP protocol**.
    
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  10. LICENSE

    of these things:
    
        a) Accompany the work with the complete corresponding
        machine-readable source code for the Library including whatever
        changes were used in the work (which must be distributed under
        Sections 1 and 2 above); and, if the work is an executable linked
        with the Library, with the complete machine-readable "work that
        uses the Library", as object code and/or source code, so that the
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