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* Add model 2024-12-16-swin_tiny_patch4_window7_224_mm_classification_pipeline_en

* Add model 2024-12-16-swin_tiny_patch4_window7_224_finetuned_eurosat_polejowska_en

* Add model 2024-12-16-swin_tiny_patch4_window7_224_finetuned_eurosat_polejowska_pipeline_en

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* Add model 2024-12-16-swin_tiny_patch4_window7_224_finetuned_cifar10_nielsr_en

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* Add model 2024-12-16-swin_tiny_patch4_window7_224_mm_classification_en

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* Add model 2024-12-16-swin_tiny_patch4_window7_224_seg_swin_amal_finetuned_eurosat_en

* Add model 2024-12-16-cards_bottom_left_swin_tiny_patch4_window7_224_finetuned_dough_100_epochs_pipeline_en

* Add model 2024-12-16-xlm_roberta_base_finetuned_panx_german_maarten1953_pipeline_en

* Add model 2024-12-16-swin_tiny_patch4_window7_224_finetuned_cifar10_nielsr_pipeline_en

* Add model 2024-12-16-somd_train_xlm_v2_en

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* Add model 2024-12-16-swin_base_patch4_window7_224_rice_disease_02_en

* Add model 2024-12-16-xlm_roberta_base_finetuned_panx_all_francois2511_en

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* Add model 2024-12-16-distilbert_base_turkish_cased_multinli_turkish_tr

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* Add model 2024-12-16-swin_base_patch4_window7_224_microsoft_en

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* Add model 2024-12-16-translate_english_tonga_tonga_islands_turkish_tr

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* Add model 2024-12-16-t5_small_finetuned_english_tonga_tonga_islands_english_pipeline_en

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---------

Co-authored-by: ahmedlone127 <[email protected]>
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---
layout: model
title: English 12_shot_sta_head_skhead MPNetEmbeddings from Nhat1904
author: John Snow Labs
name: 12_shot_sta_head_skhead
date: 2024-12-15
tags: [en, open_source, onnx, embeddings, mpnet]
task: Embeddings
language: en
edition: Spark NLP 5.5.1
spark_version: 3.0
supported: true
engine: onnx
annotator: MPNetEmbeddings
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`12_shot_sta_head_skhead` is a English model originally trained by Nhat1904.

{:.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/12_shot_sta_head_skhead_en_5.5.1_3.0_1734306650214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/12_shot_sta_head_skhead_en_5.5.1_3.0_1734306650214.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")

embeddings = MPNetEmbeddings.pretrained("12_shot_sta_head_skhead","en") \
.setInputCols(["document"]) \
.setOutputCol("embeddings")

pipeline = Pipeline().setStages([documentAssembler, embeddings])
data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)

```
```scala

val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")

val embeddings = MPNetEmbeddings.pretrained("12_shot_sta_head_skhead","en")
.setInputCols(Array("document"))
.setOutputCol("embeddings")

val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
val data = Seq("I love spark-nlp").toDF("text")
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)

```
</div>

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|12_shot_sta_head_skhead|
|Compatibility:|Spark NLP 5.5.1+|
|License:|Open Source|
|Edition:|Official|
|Input Labels:|[document]|
|Output Labels:|[mpnet]|
|Language:|en|
|Size:|407.0 MB|

## References

https://huggingface.co/Nhat1904/12_shot_STA_head_skhead
Original file line number Diff line number Diff line change
@@ -0,0 +1,69 @@
---
layout: model
title: English 12_shot_sta_head_skhead_pipeline pipeline MPNetEmbeddings from Nhat1904
author: John Snow Labs
name: 12_shot_sta_head_skhead_pipeline
date: 2024-12-15
tags: [en, open_source, pipeline, onnx]
task: Embeddings
language: en
edition: Spark NLP 5.5.1
spark_version: 3.0
supported: true
annotator: PipelineModel
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`12_shot_sta_head_skhead_pipeline` is a English model originally trained by Nhat1904.

{:.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/12_shot_sta_head_skhead_pipeline_en_5.5.1_3.0_1734306672117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/12_shot_sta_head_skhead_pipeline_en_5.5.1_3.0_1734306672117.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("12_shot_sta_head_skhead_pipeline", lang = "en")
annotations = pipeline.transform(df)

```
```scala

val pipeline = new PretrainedPipeline("12_shot_sta_head_skhead_pipeline", lang = "en")
val annotations = pipeline.transform(df)

```
</div>

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|12_shot_sta_head_skhead_pipeline|
|Type:|pipeline|
|Compatibility:|Spark NLP 5.5.1+|
|License:|Open Source|
|Edition:|Official|
|Language:|en|
|Size:|407.0 MB|

## References

https://huggingface.co/Nhat1904/12_shot_STA_head_skhead

## Included Models

- DocumentAssembler
- MPNetEmbeddings
86 changes: 86 additions & 0 deletions docs/_posts/ahmedlone127/2024-12-15-32_shot_twitter_en.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,86 @@
---
layout: model
title: English 32_shot_twitter MPNetEmbeddings from Nhat1904
author: John Snow Labs
name: 32_shot_twitter
date: 2024-12-15
tags: [en, open_source, onnx, embeddings, mpnet]
task: Embeddings
language: en
edition: Spark NLP 5.5.1
spark_version: 3.0
supported: true
engine: onnx
annotator: MPNetEmbeddings
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`32_shot_twitter` is a English model originally trained by Nhat1904.

{:.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/32_shot_twitter_en_5.5.1_3.0_1734306891116.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/32_shot_twitter_en_5.5.1_3.0_1734306891116.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")

embeddings = MPNetEmbeddings.pretrained("32_shot_twitter","en") \
.setInputCols(["document"]) \
.setOutputCol("embeddings")

pipeline = Pipeline().setStages([documentAssembler, embeddings])
data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)

```
```scala

val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")

val embeddings = MPNetEmbeddings.pretrained("32_shot_twitter","en")
.setInputCols(Array("document"))
.setOutputCol("embeddings")

val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
val data = Seq("I love spark-nlp").toDF("text")
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)

```
</div>

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|32_shot_twitter|
|Compatibility:|Spark NLP 5.5.1+|
|License:|Open Source|
|Edition:|Official|
|Input Labels:|[document]|
|Output Labels:|[mpnet]|
|Language:|en|
|Size:|406.9 MB|

## References

https://huggingface.co/Nhat1904/32-shot-twitter
69 changes: 69 additions & 0 deletions docs/_posts/ahmedlone127/2024-12-15-32_shot_twitter_pipeline_en.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,69 @@
---
layout: model
title: English 32_shot_twitter_pipeline pipeline MPNetEmbeddings from Nhat1904
author: John Snow Labs
name: 32_shot_twitter_pipeline
date: 2024-12-15
tags: [en, open_source, pipeline, onnx]
task: Embeddings
language: en
edition: Spark NLP 5.5.1
spark_version: 3.0
supported: true
annotator: PipelineModel
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`32_shot_twitter_pipeline` is a English model originally trained by Nhat1904.

{:.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/32_shot_twitter_pipeline_en_5.5.1_3.0_1734306912085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/32_shot_twitter_pipeline_en_5.5.1_3.0_1734306912085.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("32_shot_twitter_pipeline", lang = "en")
annotations = pipeline.transform(df)

```
```scala

val pipeline = new PretrainedPipeline("32_shot_twitter_pipeline", lang = "en")
val annotations = pipeline.transform(df)

```
</div>

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|32_shot_twitter_pipeline|
|Type:|pipeline|
|Compatibility:|Spark NLP 5.5.1+|
|License:|Open Source|
|Edition:|Official|
|Language:|en|
|Size:|406.9 MB|

## References

https://huggingface.co/Nhat1904/32-shot-twitter

## Included Models

- DocumentAssembler
- MPNetEmbeddings
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