2024-10-10-gemma_2_2b_it_iq3_m_en

docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_iq3_m_en.md

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+---
+layout: model
+title: English gemma_2_2b_it_iq3_m AutoGGUFModel from lmstudio-community
+author: John Snow Labs
+name: gemma_2_2b_it_iq3_m
+date: 2024-10-10
+tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow]
+task: Text Generation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: tensorflow
+annotator: AutoGGUFModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_iq3_m` is a English model prepared by lmstudio-community.
+
+{:.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/gemma_2_2b_it_iq3_m_en_5.5.0_3.0_1728575178358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq3_m_en_5.5.0_3.0_1728575178358.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
+
+document = DocumentAssembler() \
+       .setInputCol("text") \
+       .setOutputCol("document")
+
+autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq3_m","en") \
+    .setInputCols(["document"]) \
+    .setOutputCol("completions") \
+    .setBatchSize(4) \
+    .setNPredict(20) \
+    .setNGpuLayers(99) \
+    .setTemperature(0.4) \
+    .setTopK(40) \
+    .setTopP(0.9) \
+    .setPenalizeNl(True)
+
+pipeline = Pipeline().setStages([document, autoGGUFModel])
+data = spark.createDataFrame([["Hello, I am a"]]).toDF("text")
+result = pipeline.fit(data).transform(data)
+result.select("completions").show(truncate = False)
+
+```
+```scala
+
+val document = new DocumentAssembler()
+     .setInputCol("text")
+     .setOutputCol("document")
+
+val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq3_m", "en")
+  .setInputCols("document")
+  .setOutputCol("completions")
+  .setBatchSize(4)
+  .setNPredict(20)
+  .setNGpuLayers(99)
+  .setTemperature(0.4f)
+  .setTopK(40)
+  .setTopP(0.9f)
+  .setPenalizeNl(true)
+
+val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel))
+
+val data = Seq("Hello, I am a").toDF("text")
+val result = pipeline.fit(data).transform(data)
+result.select("completions").show(truncate = false)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gemma_2_2b_it_iq3_m|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[completions]|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF

docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_iq4_xs_en.md

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+---
+layout: model
+title: English gemma_2_2b_it_iq4_xs AutoGGUFModel from lmstudio-community
+author: John Snow Labs
+name: gemma_2_2b_it_iq4_xs
+date: 2024-10-10
+tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow]
+task: Text Generation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: tensorflow
+annotator: AutoGGUFModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_iq4_xs` is a English model prepared by lmstudio-community.
+
+{:.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/gemma_2_2b_it_iq4_xs_en_5.5.0_3.0_1728575247990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq4_xs_en_5.5.0_3.0_1728575247990.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
+
+document = DocumentAssembler() \
+       .setInputCol("text") \
+       .setOutputCol("document")
+
+autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq4_xs","en") \
+    .setInputCols(["document"]) \
+    .setOutputCol("completions") \
+    .setBatchSize(4) \
+    .setNPredict(20) \
+    .setNGpuLayers(99) \
+    .setTemperature(0.4) \
+    .setTopK(40) \
+    .setTopP(0.9) \
+    .setPenalizeNl(True)
+
+pipeline = Pipeline().setStages([document, autoGGUFModel])
+data = spark.createDataFrame([["Hello, I am a"]]).toDF("text")
+result = pipeline.fit(data).transform(data)
+result.select("completions").show(truncate = False)
+
+```
+```scala
+
+val document = new DocumentAssembler()
+     .setInputCol("text")
+     .setOutputCol("document")
+
+val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq4_xs", "en")
+  .setInputCols("document")
+  .setOutputCol("completions")
+  .setBatchSize(4)
+  .setNPredict(20)
+  .setNGpuLayers(99)
+  .setTemperature(0.4f)
+  .setTopK(40)
+  .setTopP(0.9f)
+  .setPenalizeNl(true)
+
+val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel))
+
+val data = Seq("Hello, I am a").toDF("text")
+val result = pipeline.fit(data).transform(data)
+result.select("completions").show(truncate = false)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gemma_2_2b_it_iq4_xs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[completions]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF

docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q3_k_l_en.md

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+---
+layout: model
+title: English gemma_2_2b_it_q3_k_l AutoGGUFModel from lmstudio-community
+author: John Snow Labs
+name: gemma_2_2b_it_q3_k_l
+date: 2024-10-10
+tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow]
+task: Text Generation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: tensorflow
+annotator: AutoGGUFModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q3_k_l` is a English model prepared by lmstudio-community.
+
+{:.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/gemma_2_2b_it_q3_k_l_en_5.5.0_3.0_1728575314785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q3_k_l_en_5.5.0_3.0_1728575314785.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
+
+document = DocumentAssembler() \
+       .setInputCol("text") \
+       .setOutputCol("document")
+
+autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q3_k_l","en") \
+    .setInputCols(["document"]) \
+    .setOutputCol("completions") \
+    .setBatchSize(4) \
+    .setNPredict(20) \
+    .setNGpuLayers(99) \
+    .setTemperature(0.4) \
+    .setTopK(40) \
+    .setTopP(0.9) \
+    .setPenalizeNl(True)
+
+pipeline = Pipeline().setStages([document, autoGGUFModel])
+data = spark.createDataFrame([["Hello, I am a"]]).toDF("text")
+result = pipeline.fit(data).transform(data)
+result.select("completions").show(truncate = False)
+
+```
+```scala
+
+val document = new DocumentAssembler()
+     .setInputCol("text")
+     .setOutputCol("document")
+
+val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q3_k_l", "en")
+  .setInputCols("document")
+  .setOutputCol("completions")
+  .setBatchSize(4)
+  .setNPredict(20)
+  .setNGpuLayers(99)
+  .setTemperature(0.4f)
+  .setTopK(40)
+  .setTopP(0.9f)
+  .setPenalizeNl(true)
+
+val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel))
+
+val data = Seq("Hello, I am a").toDF("text")
+val result = pipeline.fit(data).transform(data)
+result.select("completions").show(truncate = false)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gemma_2_2b_it_q3_k_l|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[completions]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF