2024-09-03-xlmroberta_ner_base_indonesian_pipeline_id

docs/_posts/ahmedlone127/2024-09-01-albert_base_finetuned_recipe_modified_en.md

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+---
+layout: model
+title: English albert_base_finetuned_recipe_modified AlbertForQuestionAnswering from saumyasinha0510
+author: John Snow Labs
+name: albert_base_finetuned_recipe_modified
+date: 2024-09-01
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_finetuned_recipe_modified` is a English model originally trained by saumyasinha0510.
+
+{:.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/albert_base_finetuned_recipe_modified_en_5.4.2_3.0_1725193374690.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_finetuned_recipe_modified_en_5.4.2_3.0_1725193374690.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 = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_finetuned_recipe_modified","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_finetuned_recipe_modified", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_finetuned_recipe_modified|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/saumyasinha0510/Albert-base-finetuned-recipe-modified

docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_k_fold_1_en.md

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+---
+layout: model
+title: English albert_base_qa_2_k_fold_1 AlbertForQuestionAnswering from mateiaass
+author: John Snow Labs
+name: albert_base_qa_2_k_fold_1
+date: 2024-09-01
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_k_fold_1` is a English model originally trained by mateiaass.
+
+{:.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/albert_base_qa_2_k_fold_1_en_5.4.2_3.0_1725193498781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_1_en_5.4.2_3.0_1725193498781.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 = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_k_fold_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_k_fold_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_qa_2_k_fold_1|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/mateiaass/albert-base-qa-2-k-fold-1

docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_entity_selection_5771228_en.md

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+---
+layout: model
+title: English BertForSequenceClassification Cased model (from kamivao)
+author: John Snow Labs
+name: bert_classifier_autonlp_entity_selection_5771228
+date: 2024-09-01
+tags: [en, open_source, bert, sequence_classification, classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-entity_selection-5771228` is a English model originally trained by `kamivao`.
+
+## Predicted Entities
+
+`1`, `0`
+
+{:.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/bert_classifier_autonlp_entity_selection_5771228_en_5.4.2_3.0_1725204813533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_entity_selection_5771228_en_5.4.2_3.0_1725204813533.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() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autonlp_entity_selection_5771228","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])
+
+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 seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autonlp_entity_selection_5771228","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.classify.bert.by_kamivao").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_autonlp_entity_selection_5771228|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/kamivao/autonlp-entity_selection-5771228

docs/_posts/ahmedlone127/2024-09-01-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline_en.md

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+---
+layout: model
+title: English bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline pipeline BertForQuestionAnswering from anas-awadalla
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline` is a English model originally trained by anas-awadalla.
+
+{:.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/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline_en_5.4.2_3.0_1725185371351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline_en_5.4.2_3.0_1725185371351.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
+
+pipeline = PretrainedPipeline("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|386.6 MB|
+
+## References
+
+https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-6
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering