2023-03-01-roberta_token_classifier_large_ontonotes5_la (#13589)

* Add model 2023-03-01-roberta_token_classifier_large_ontonotes5_la * Add model 2023-03-01-roberta_token_classifier_base_ner_demo_mn * Add model 2023-03-01-roberta_token_classifier_fullstop_catalan_punctuation_prediction_ca * Add model 2023-03-01-roberta_token_classifier_slovakbert_ner_sk * Add model 2023-03-01-roberta_token_classifier_bertin_base_pos_conll2002_es * Add model 2023-03-01-roberta_token_classifier_bertin_base_ner_conll2002_es * Add model 2023-03-01-roberta_token_classifier_ticker_en * Add model 2023-03-03-distilbert_token_classifier_ner_roles_openapi_en * Add model 2023-03-03-distilbert_token_classifier_base_ner_en * Add model 2023-03-03-distilbert_token_classifier_cpener_test_en * Add model 2023-03-03-distilbert_token_classifier_base_uncased_ft_conll2003_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_inspec_en * Add model 2023-03-03-distilbert_token_classifier_base_uncased_finetuned_conll2003_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_job_all_903929564_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_all_903429548_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_vs_all_902129475_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824211_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_ner_778023879_en * Add model 2023-03-03-dtilbert_token_classifier_typo_detector_is * Add model 2023-03-03-distilbert_token_classifier_icelandic_ner_distilbert_is * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_kptimes_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_openkp_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_all_903429540_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_all_904029577_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_vsv_all_901529445_en * Add model 2023-03-03-distilbert_token_classifier_ner_roles_openapi_en * Add model 2023-03-03-distilbert_token_classifier_base_uncased_ft_conll2003_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_kptimes_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_inspec_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_all_904029577_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_all_904029569_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_all_903429540_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_vsv_all_901529445_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824218_en * Add model 2023-03-03-dtilbert_token_classifier_typo_detector_is * Add model 2023-03-03-distilbert_tok_classifier_typo_detector_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_job_all_903929564_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_all_903429548_en * Add model 2023-03-03-distilbert_token_classifier_base_ner_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824211_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824209_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_openkp_en * Add model 2023-03-03-distilbert_token_classifier_cpener_test_en * Add model 2023-03-03-distilbert_token_classifier_base_uncased_finetuned_conll2003_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824218_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_ner_778023879_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_vs_all_902129475_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824209_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_all_904029569_en * Add model 2023-03-03-distilbert_tok_classifier_typo_detector_en * Add model 2023-03-03-distilbert_token_classifier_icelandic_ner_distilbert_is * Add model 2023-03-03-distilbert_token_classifier_base_ner_en * Add model 2023-03-03-distilbert_token_classifier_cpener_test_en * Add model 2023-03-03-distilbert_token_classifier_base_uncased_ft_conll2003_en * Add model 2023-03-03-distilbert_token_classifier_base_uncased_finetuned_conll2003_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_all_904029577_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_all_904029569_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_vsv_all_901529445_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824211_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824218_en * Add model 2023-03-03-distilbert_token_classifier_ner_roles_openapi_en * Add model 2023-03-03-distilbert_token_classifier_ner_roles_openapi_en * Add model 2023-03-03-distilbert_token_classifier_base_uncased_ft_conll2003_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_inspec_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_openkp_en * Add model 2023-03-03-distilbert_token_classifier_base_uncased_finetuned_conll2003_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_all_904029577_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_all_903429548_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824211_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824218_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_final_784824209_en * Add model 2023-03-03-dtilbert_token_classifier_typo_detector_is * Add model 2023-03-03-distilbert_token_classifier_icelandic_ner_distilbert_is * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_vs_all_902129475_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_all_903429548_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_inspec_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_kptimes_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_vs_all_902129475_en * Add model 2023-03-03-distilbert_token_classifier_base_ner_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_vsv_all_901529445_en * Add model 2023-03-03-distilbert_tok_classifier_typo_detector_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_kptimes_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_job_all_903929564_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_name_all_904029569_en * Add model 2023-03-03-distilbert_token_classifier_cpener_test_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_ner_778023879_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_all_903429540_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_job_all_903929564_en * Add model 2023-03-03-distilbert_token_classifier_keyphrase_extraction_openkp_en * Add model 2023-03-03-distilbert_token_classifier_autotrain_company_all_903429540_en --------- Co-authored-by: gokhanturer <mgturer@gmail.com>
JohnSnowLabs · Mar 5, 2023 · d6b151f · d6b151f
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diff --git a/docs/_posts/gokhanturer/2023-03-01-roberta_token_classifier_base_ner_demo_mn.md b/docs/_posts/gokhanturer/2023-03-01-roberta_token_classifier_base_ner_demo_mn.md
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+---
+layout: model
+title: Mongolian RobertaForTokenClassification Base Cased model (from onon214)
+author: John Snow Labs
+name: roberta_token_classifier_base_ner_demo
+date: 2023-03-01
+tags: [mn, open_source, roberta, token_classification, ner, tensorflow]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 4.3.0
+spark_version: 3.0
+supported: true
+engine: tensorflow
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-ner-demo` is a Mongolian model originally trained by `onon214`.
+
+## Predicted Entities
+
+`MISC`, `LOC`, `PER`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_token_classifier_base_ner_demo_mn_4.3.0_3.0_1677703536380.zip){:.button.button-orange}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_token_classifier_base_ner_demo_mn_4.3.0_3.0_1677703536380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCols(["text"]) \
+    .setOutputCols("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+tokenClassifier = RobertaForTokenClassification.pretrained("roberta_token_classifier_base_ner_demo","mn") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCols(Array("text")) 
+    .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RobertaForTokenClassification.pretrained("roberta_token_classifier_base_ner_demo","mn") 
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_token_classifier_base_ner_demo|
+|Compatibility:|Spark NLP 4.3.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|mn|
+|Size:|466.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|128|
+
+## References
+
+- https://huggingface.co/onon214/roberta-base-ner-demo
diff --git a/...gokhanturer/2023-03-01-roberta_token_classifier_bertin_base_ner_conll2002_es.md b/...gokhanturer/2023-03-01-roberta_token_classifier_bertin_base_ner_conll2002_es.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: Spanish RobertaForTokenClassification Base Cased model (from bertin-project)
+author: John Snow Labs
+name: roberta_token_classifier_bertin_base_ner_conll2002
+date: 2023-03-01
+tags: [es, open_source, roberta, token_classification, ner, tensorflow]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 4.3.0
+spark_version: 3.0
+supported: true
+engine: tensorflow
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bertin-base-ner-conll2002-es` is a Spanish model originally trained by `bertin-project`.
+
+## Predicted Entities
+
+`MISC`, `LOC`, `PER`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_token_classifier_bertin_base_ner_conll2002_es_4.3.0_3.0_1677703750308.zip){:.button.button-orange}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_token_classifier_bertin_base_ner_conll2002_es_4.3.0_3.0_1677703750308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCols(["text"]) \
+    .setOutputCols("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+tokenClassifier = RobertaForTokenClassification.pretrained("roberta_token_classifier_bertin_base_ner_conll2002","es") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCols(Array("text")) 
+    .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RobertaForTokenClassification.pretrained("roberta_token_classifier_bertin_base_ner_conll2002","es") 
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_token_classifier_bertin_base_ner_conll2002|
+|Compatibility:|Spark NLP 4.3.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|426.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|128|
+
+## References
+
+- https://huggingface.co/bertin-project/bertin-base-ner-conll2002-es
diff --git a/...gokhanturer/2023-03-01-roberta_token_classifier_bertin_base_pos_conll2002_es.md b/...gokhanturer/2023-03-01-roberta_token_classifier_bertin_base_pos_conll2002_es.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: Spanish RobertaForTokenClassification Base Cased model (from bertin-project)
+author: John Snow Labs
+name: roberta_token_classifier_bertin_base_pos_conll2002
+date: 2023-03-01
+tags: [es, open_source, roberta, token_classification, ner, tensorflow]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 4.3.0
+spark_version: 3.0
+supported: true
+engine: tensorflow
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bertin-base-pos-conll2002-es` is a Spanish model originally trained by `bertin-project`.
+
+## Predicted Entities
+
+`DA`, `VAM`, `I`, `VSM`, `PP`, `VSS`, `DI`, `AQ`, `Y`, `VMN`, `Fit`, `Fg`, `Fia`, `Fpa`, `Fat`, `VSN`, `Fpt`, `DD`, `VAP`, `SP`, `NP`, `Fh`, `VAI`, `CC`, `Fd`, `VMG`, `NC`, `PX`, `DE`, `Fz`, `PN`, `Fx`, `Faa`, `Fs`, `Fe`, `VSP`, `DP`, `VAS`, `VSG`, `PT`, `Ft`, `VAN`, `PI`, `P0`, `RG`, `RN`, `CS`, `DN`, `VMI`, `Fp`, `Fc`, `PR`, `VSI`, `AO`, `VMM`, `PD`, `VMS`, `DT`, `Z`, `VMP`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_token_classifier_bertin_base_pos_conll2002_es_4.3.0_3.0_1677703697571.zip){:.button.button-orange}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_token_classifier_bertin_base_pos_conll2002_es_4.3.0_3.0_1677703697571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCols(["text"]) \
+    .setOutputCols("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+tokenClassifier = RobertaForTokenClassification.pretrained("roberta_token_classifier_bertin_base_pos_conll2002","es") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCols(Array("text")) 
+    .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RobertaForTokenClassification.pretrained("roberta_token_classifier_bertin_base_pos_conll2002","es") 
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_token_classifier_bertin_base_pos_conll2002|
+|Compatibility:|Spark NLP 4.3.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|426.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|128|
+
+## References
+
+- https://huggingface.co/bertin-project/bertin-base-pos-conll2002-es