2024-11-02-Nomic_Embed_Text_v1.5.Q8_0.gguf_en

docs/_posts/DevinTDHa/2024-11-02-Nomic_Embed_Text_v1.5.Q8_0.gguf_en.md

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+---
+layout: model
+title: nomic-embed-text-v1.5.Q8_0.gguf
+author: John Snow Labs
+name: Nomic_Embed_Text_v1.5.Q8_0.gguf
+date: 2024-11-02
+tags: [gguf, nomic, embeddings, open_source, en, llamacpp]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.2
+spark_version: 3.4
+supported: true
+engine: llamacpp
+annotator: AutoGGUFEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+nomic-embed-text is a 8192 context length text encoder that surpasses OpenAI text-embedding-ada-002 and text-embedding-3-small performance on short and long context tasks.
+
+This model is the updated 1.5 version.
+
+Original model from https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
+
+## Predicted Entities
+
+
+
+{:.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/Nomic_Embed_Text_v1.5.Q8_0.gguf_en_5.5.2_3.4_1730556912139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/Nomic_Embed_Text_v1.5.Q8_0.gguf_en_5.5.2_3.4_1730556912139.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
+import sparknlp
+from sparknlp.base import *
+from sparknlp.annotator import *
+from pyspark.ml import Pipeline
+document = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+autoGGUFModel = AutoGGUFModel.pretrained() \
+    .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([[The moons of Jupiter are 77 in total, with 79 confirmed natural satellites and 2 man-made ones."]]).toDF("text")
+result = pipeline.fit(data).transform(data)
+result.select("completions").show(truncate = False)
+```
+```scala
+import com.johnsnowlabs.nlp.base._
+import com.johnsnowlabs.nlp.annotator._
+import org.apache.spark.ml.Pipeline
+import spark.implicits._
+
+val document = new DocumentAssembler().setInputCol("text").setOutputCol("document")
+
+val autoGGUFModel = AutoGGUFEmbeddings
+  .pretrained()
+  .setInputCols("document")
+  .setOutputCol("embeddings")
+  .setBatchSize(4)
+  .setPoolingType("MEAN")
+
+val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel))
+
+val data = Seq(
+  "The moons of Jupiter are 77 in total, with 79 confirmed natural satellites and 2 man-made ones.")
+  .toDF("text")
+val result = pipeline.fit(data).transform(data)
+result.select("embeddings.embeddings").show(truncate = false)
+
+```
+</div>
+
+## Results
+
+```bash
++--------------------------------------------------------------------------------+
+|                                                                      embeddings|
++--------------------------------------------------------------------------------+
+|[[-0.034486726, 0.07770534, -0.15982522, -0.017873349, 0.013914132, 0.0365736...|
++--------------------------------------------------------------------------------+
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|Nomic_Embed_Text_v1.5.Q8_0.gguf|
+|Compatibility:|Spark NLP 5.5.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|140.7 MB|