Error while trying to load nlu.load('embed_sentence.bert')

[arvindacodes]

I am trying to create sentence similarity model using Spark_nlp, but i am getting the below two different errors.

sent_small_bert_L2_128 download started this may take some time.
Approximate size to download 16.1 MB
[OK!]

IllegalArgumentException Traceback (most recent call last)
File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\nlu\pipe\component_resolution.py:276, in get_trained_component_for_nlp_model_ref(lang, nlu_ref, nlp_ref, license_type, model_configs)
274 if component.get_pretrained_model:
275 component = component.set_metadata(
--> 276 component.get_pretrained_model(nlp_ref, lang, model_bucket),
277 nlu_ref, nlp_ref, lang, False, license_type)
278 else:

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\nlu\components\embeddings\sentence_bert\BertSentenceEmbedding.py:13, in BertSentence.get_pretrained_model(name, language, bucket)
11 @staticmethod
12 def get_pretrained_model(name, language, bucket=None):
---> 13 return BertSentenceEmbeddings.pretrained(name,language,bucket)
14 .setInputCols('sentence')
15 .setOutputCol("sentence_embeddings")

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\sparknlp\annotator\embeddings\bert_sentence_embeddings.py:231, in BertSentenceEmbeddings.pretrained(name, lang, remote_loc)
230 from sparknlp.pretrained import ResourceDownloader
--> 231 return ResourceDownloader.downloadModel(BertSentenceEmbeddings, name, lang, remote_loc)

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\sparknlp\pretrained\resource_downloader.py:40, in ResourceDownloader.downloadModel(reader, name, language, remote_loc, j_dwn)
39 try:
---> 40 j_obj = _internal._DownloadModel(reader.name, name, language, remote_loc, j_dwn).apply()
41 except Py4JJavaError as e:

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\sparknlp\internal_init_.py:317, in _DownloadModel.init(self, reader, name, language, remote_loc, validator)
316 def init(self, reader, name, language, remote_loc, validator):
--> 317 super(_DownloadModel, self).init("com.johnsnowlabs.nlp.pretrained." + validator + ".downloadModel", reader,
318 name, language, remote_loc)

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\sparknlp\internal\extended_java_wrapper.py:26, in ExtendedJavaWrapper.init(self, java_obj, *args)
25 self.sc = SparkContext._active_spark_context
---> 26 self._java_obj = self.new_java_obj(java_obj, *args)
27 self.java_obj = self._java_obj

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\sparknlp\internal\extended_java_wrapper.py:36, in ExtendedJavaWrapper.new_java_obj(self, java_class, *args)
35 def new_java_obj(self, java_class, *args):
---> 36 return self._new_java_obj(java_class, *args)

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\pyspark\ml\wrapper.py:69, in JavaWrapper._new_java_obj(java_class, *args)
68 java_args = [_py2java(sc, arg) for arg in args]
---> 69 return java_obj(*java_args)

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\py4j\java_gateway.py:1304, in JavaMember.call(self, *args)
1303 answer = self.gateway_client.send_command(command)
-> 1304 return_value = get_return_value(
1305 answer, self.gateway_client, self.target_id, self.name)
1307 for temp_arg in temp_args:

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\pyspark\sql\utils.py:134, in capture_sql_exception..deco(*a, **kw)
131 if not isinstance(converted, UnknownException):
132 # Hide where the exception came from that shows a non-Pythonic
133 # JVM exception message.
--> 134 raise_from(converted)
135 else:

File :3, in raise_from(e)

IllegalArgumentException: requirement failed: Was not found appropriate resource to download for request: ResourceRequest(sent_small_bert_L2_128,Some(en),public/models,4.0.2,3.3.0) with downloader: com.johnsnowlabs.nlp.pretrained.S3ResourceDownloader@c7c973f

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last)
File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\nlu_init_.py:234, in load(request, path, verbose, gpu, streamlit_caching, m1_chip)
233 continue
--> 234 nlu_component = nlu_ref_to_component(nlu_ref)
235 # if we get a list of components, then the NLU reference is a pipeline, we do not need to check order

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\nlu\pipe\component_resolution.py:160, in nlu_ref_to_component(nlu_ref, detect_lang, authenticated)
159 else:
--> 160 resolved_component = get_trained_component_for_nlp_model_ref(lang, nlu_ref, nlp_ref, license_type, model_params)
162 if resolved_component is None:

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\nlu\pipe\component_resolution.py:287, in get_trained_component_for_nlp_model_ref(lang, nlu_ref, nlp_ref, license_type, model_configs)
286 except Exception as e:
--> 287 raise ValueError(f'Failure making component, nlp_ref={nlp_ref}, nlu_ref={nlu_ref}, lang={lang}, \n err={e}')
289 return component

ValueError: Failure making component, nlp_ref=sent_small_bert_L2_128, nlu_ref=embed_sentence.bert, lang=en,
err=requirement failed: Was not found appropriate resource to download for request: ResourceRequest(sent_small_bert_L2_128,Some(en),public/models,4.0.2,3.3.0) with downloader: com.johnsnowlabs.nlp.pretrained.S3ResourceDownloader@c7c973f

During handling of the above exception, another exception occurred:

Exception Traceback (most recent call last)
Cell In [16], line 2
1 import nlu
----> 2 pipe = nlu.load('embed_sentence.bert')
3 print("pipe",pipe)

File c:\users\ramesar2\appdata\local\programs\python\python38\lib\site-packages\nlu_init_.py:249, in load(request, path, verbose, gpu, streamlit_caching, m1_chip)
247 print(e[1])
248 print(err)
--> 249 raise Exception(
250 f"Something went wrong during creating the Spark NLP model_anno_obj for your request = {request} Did you use a NLU Spell?")
251 # Complete Spark NLP Pipeline, which is defined as a DAG given by the starting Annotators
252 try:

Exception: Something went wrong during creating the Spark NLP model_anno_obj for your request = embed_sentence.bert Did you use a NLU Spell?

[maziyarpanahi]

Transferring here since it's nlu package. (just in case, you need all these steps correctly followed in order to use Apache Spark on Windows: https://nlp.johnsnowlabs.com/docs/en/install#windows-support)