class_docstr: Downloads and manages resources, pretrained models/pipelines.
  
  Usually you will not need to use this class directly. It is called by the
  `pretrained()` function of annotators.
  
  However, you can use this class to list the available pretrained resources.
  
  Examples
  --------
  If you want to list all NerDLModels for the english language you can run:
  
  >>> ResourceDownloader.showPublicModels("NerDLModel", "en")
  +-------------+------+---------+
  | Model       | lang | version |
  +-------------+------+---------+
  | onto_100    | en   | 2.1.0   |
  | onto_300    | en   | 2.1.0   |
  | ner_dl_bert | en   | 2.2.0   |
  |  ...        | ...  | ...     |
  
  
  Similarly for Pipelines:
  
  >>> ResourceDownloader.showPublicPipelines("en")
  +------------------+------+---------+
  | Pipeline         | lang | version |
  +------------------+------+---------+
  | dependency_parse | en   | 2.0.2   |
  | check_spelling   | en   | 2.1.0   |
  | match_datetime   | en   | 2.1.0   |
  |  ...             | ...  | ...     |
docstr: Downloads a model directly to the cache folder.
  You can use to copy-paste the s3 URI from the model hub  and download the model.
  For available s3 URI and models, please see the `Models Hub <https://sparknlp.org/models>`__.
  Parameters
  ----------
  name : str
      Name of the model or s3 URI
  remote_loc : str, optional
      Directory of the remote Spark NLP Folder, by default "public/models"
  unzip : Bool, optional
      Used to unzip model, by default 'True'
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code: def downloadModelDirectly(
      name, remote_loc="public/models", unzip=True
  ):
      """Downloads a model directly to the cache folder.
      You can use to copy-paste the s3 URI from the model hub  and download the model.
      For available s3 URI and models, please see the `Models Hub <https://sparknlp.org/models>`__.
      Parameters
      ----------
      name : str
          Name of the model or s3 URI
      remote_loc : str, optional
          Directory of the remote Spark NLP Folder, by default "public/models"
      unzip : Bool, optional
          Used to unzip model, by default 'True'
      """
      _internal._DownloadModelDirectly(name, remote_loc, unzip).apply()
  
file_path: spark-nlp/python/sparknlp/pretrained/resource_downloader.py
imports: import sys
  import threading
  from py4j.protocol import Py4JJavaError
  from pyspark.ml import PipelineModel
  import sparknlp.internal
  from sparknlp.pretrained.utils import printProgress
label_desc: Use image node_id 2 for calling the ResourceDownloader obj's underlying member method code with example usage: obj.downloadModelDirectly(name, remote_loc, unzip) without return types