2024-07-16-snowflake_artic_m_en

docs/_posts/ahmedlone127/2024-07-16-mxbai_large_v1_en.md

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+---
+layout: model
+title: mxbai large Model
+author: John Snow Labs
+name: mxbai_large_v1
+date: 2024-07-16
+tags: [embeddings, mxbai, en, open_source, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MxbaiEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MxbaiEmbeddings, adataped from huggingface imported to Spark-NLP to provide scalability and production-readiness.
+
+{:.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/mxbai_large_v1_en_5.4.2_3.0_1721143405168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mxbai_large_v1_en_5.4.2_3.0_1721143405168.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')
+
+mxbai = MxbaiEmbeddings.pretrained("mxbai_large_v1","en") \
+    .setInputCols("document") \
+    .setOutputCol("embeddings") \
+
+pipeline = Pipeline().setStages([documentAssembler, mxbai])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val mxbai = MxbaiEmbeddings.pretrained("mxbai_large_v1", "en")
+    .setInputCols("documents")
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, mxbai))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mxbai_large_v1|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[Mxbai]|
+|Language:|en|
+|Size:|793.8 MB|

docs/_posts/ahmedlone127/2024-07-16-snowflake_artic_m_en.md

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+---
+layout: model
+title: SnowFlake Medium Model
+author: John Snow Labs
+name: snowflake_artic_m
+date: 2024-07-16
+tags: [embeddings, snowflake, en, open_source, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SnowFlakeEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SnowFlakeEmbeddings, adataped from huggingface imported to Spark-NLP to provide scalability and production-readiness.
+
+{:.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/snowflake_artic_m_en_5.4.2_3.0_1721136236413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snowflake_artic_m_en_5.4.2_3.0_1721136236413.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')
+
+snowflake = SnowFlakeEmbeddings.pretrained("snowflake_artic_m","en") \
+    .setInputCols("document") \
+    .setOutputCol("embeddings") \
+
+pipeline = Pipeline().setStages([documentAssembler, snowflake])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val snowflake = SnowFlakeEmbeddings.pretrained("snowflake_artic_m", "en")
+    .setInputCols("documents")
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, snowflake))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|snowflake_artic_m|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[snowflake]|
+|Language:|en|
+|Size:|405.7 MB|

docs/_posts/ahmedlone127/2024-07-19-image_classifier_vit_base_patch16_224_en.md

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+---
+layout: model
+title: English image_classifier_vit_base_patch16_224 ViTForImageClassification from google
+author: John Snow Labs
+name: image_classifier_vit_base_patch16_224
+date: 2024-07-19
+tags: [vit, image_classification, en, open_source, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained VIT model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_base_patch16_224 is a English model originally trained by google.
+
+{:.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/image_classifier_vit_base_patch16_224_en_5.4.2_3.0_1721418812161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_vit_base_patch16_224_en_5.4.2_3.0_1721418812161.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
+
+image_assembler = ImageAssembler()     .setInputCol("image") \
+    .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification \
+    .pretrained("image_classifier_vit_base_patch16_224", "en")    .setInputCols("image_assembler") \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+    image_assembler,
+    imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+.setInputCol("image")
+.setOutputCol("image_assembler")
+
+val imageClassifier = ViTForImageClassification
+.pretrained("image_classifier_vit_base_patch16_224", "en")
+.setInputCols("image_assembler")
+.setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classifier_vit_base_patch16_224|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|324.0 MB|

docs/_posts/ahmedlone127/2024-07-20-image_classifier_convnext_tiny_224_local_en.md

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+---
+layout: model
+title: English image_classifier_convnext_tiny_224_local ConvNextForImageClassification
+author: John Snow Labs
+name: image_classifier_convnext_tiny_224_local
+date: 2024-07-20
+tags: [imagenet, image_classification, en, open_source, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ConvNextForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ConvNext model for Image Classification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.
+
+The ConvNeXT model was proposed in A ConvNet for the 2020s by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie.
+
+{:.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/image_classifier_convnext_tiny_224_local_en_5.4.2_3.0_1721500815172.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_convnext_tiny_224_local_en_5.4.2_3.0_1721500815172.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
+
+image_assembler = ImageAssembler()     .setInputCol("image") \
+    .setOutputCol("image_assembler")
+
+imageClassifier = ConvNextForImageClassification \
+    .pretrained("image_classifier_convnext_tiny_224_local", "en")    .setInputCols("image_assembler") \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+    image_assembler,
+    imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+.setInputCol("image")
+.setOutputCol("image_assembler")
+
+val imageClassifier = ConvNextForImageClassification
+.pretrained("image_classifier_convnext_tiny_224_local", "en")
+.setInputCols("image_assembler")
+.setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classifier_convnext_tiny_224_local|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|107.2 MB|