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object SparkNLP

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  4. val MavenGpuSpark3: String
  5. val MavenSpark3: String
  6. val MavenSparkAarch64: String
  7. val MavenSparkSilicon: String
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  20. def start(gpu: Boolean = false, apple_silicon: Boolean = false, aarch64: Boolean = false, memory: String = "16G", cache_folder: String = "", log_folder: String = "", cluster_tmp_dir: String = "", params: Map[String, String] = Map.empty): SparkSession

    Start SparkSession with Spark NLP

    Start SparkSession with Spark NLP

    gpu

    start Spark NLP with GPU

    apple_silicon

    start Spark NLP for Apple M1 & M2 systems

    aarch64

    start Spark NLP for Linux Aarch64 systems

    memory

    set driver memory for SparkSession

    cache_folder

    The location to download and extract pretrained Models and Pipelines (by default, it will be in the users home directory under cache_pretrained.)

    log_folder

    The location to use on a cluster for temporarily files such as unpacking indexes for WordEmbeddings. By default, this locations is the location of hadoop.tmp.dir set via Hadoop configuration for Apache Spark. NOTE: S3 is not supported and it must be local, HDFS, or DBFS.

    cluster_tmp_dir

    The location to save logs from annotators during training (By default, it will be in the users home directory under annotator_logs.)

    params

    Custom parameters to set for the Spark configuration (Default: Map.empty)

    returns

    SparkSession

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