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: Clears the cache entry of a model.
  
  Parameters
  ----------
  name : str
      Name of the model
  language : en
      Language of the model
  remote_loc : str, optional
      Directory of the remote Spark NLP Folder, by default None
docstr_tok: ["Clears","the","cache","entry","of","a","model",".","Parameters","--","--","--","--","--","name",":","str","Name","of","the","model","language",":","en","Language","of","the","model","remote_loc",":","str",",","optional","Directory","of","the","remote","Spark","NLP","Folder",",","by","default","None"]
code: def clearCache(name, language, remote_loc=None):
      """Clears the cache entry of a model.
  
      Parameters
      ----------
      name : str
          Name of the model
      language : en
          Language of the model
      remote_loc : str, optional
          Directory of the remote Spark NLP Folder, by default None
      """
      _internal._ClearCache(name, language, remote_loc).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 4 for calling the ResourceDownloader obj's underlying member method code with example usage: obj.clearCache(name, language, remote_loc) without return types