SparkNLP 1033: Introducing LLAVA

CHANGELOG

@@ -1,3 +1,36 @@
+========
+5.5.1
+========
+----------------
+New Features & Enhancements
+----------------
+* `BertForMultipleChoice` Transformer Added. Enhanced BERT’s capabilities to handle multiple-choice tasks such as standardized test questions and survey or quiz automation.
+* Integrated New Tasks and Documentation:
+  * Added support and documentation for the following tasks:
+  * Automatic Speech Recognition
+  * Dependency Parsing
+  * Image Captioning
+  * Image Classification
+  * Landing Page
+  * Question Answering
+  * Summarization
+  * Table Question Answering
+  * Text Classification
+  * Text Generation
+  * Text Preprocessing
+  * Token Classification
+  * Translation
+  * Zero-Shot Classification
+  * Zero-Shot Image Classification
+* `PromptAssembler` Annotator Introduced. Introduced a new annotator that constructs prompts for LLMs using a chat template and a sequence of messages. Accepts an array of tuples with roles (“system”, “user”, “assistant”) and message texts. Utilizes llama.cpp as a backend for template parsing, supporting basic template applications.
+
+----------------
+Bug Fixes
+----------------
+* Resolved Pretrained Model Loading Issue on DBFS Systems.
+* Fixed a bug where pretrained models were not found when running AutoGGUF model pipelines on Databricks due to incorrect path handling of gguf files.
+
+
 ========
 5.5.0
 ========

README.md

@@ -63,7 +63,7 @@ $ java -version
 $ conda create -n sparknlp python=3.7 -y
 $ conda activate sparknlp
 # spark-nlp by default is based on pyspark 3.x
-$ pip install spark-nlp==5.5.0 pyspark==3.3.1
+$ pip install spark-nlp==5.5.1 pyspark==3.3.1
 ```
 
 In Python console or Jupyter `Python3` kernel:
@@ -129,7 +129,7 @@ For a quick example of using pipelines and models take a look at our official [d
 
 ### Apache Spark Support
 
-Spark NLP *5.5.0* has been built on top of Apache Spark 3.4 while fully supports Apache Spark 3.0.x, 3.1.x, 3.2.x, 3.3.x, 3.4.x, and 3.5.x
+Spark NLP *5.5.1* has been built on top of Apache Spark 3.4 while fully supports Apache Spark 3.0.x, 3.1.x, 3.2.x, 3.3.x, 3.4.x, and 3.5.x
 
 | Spark NLP | Apache Spark 3.5.x | Apache Spark 3.4.x | Apache Spark 3.3.x | Apache Spark 3.2.x | Apache Spark 3.1.x | Apache Spark 3.0.x | Apache Spark 2.4.x | Apache Spark 2.3.x |
 |-----------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|
@@ -157,7 +157,7 @@ Find out more about 4.x `SparkNLP` versions in our official [documentation](http
 
 ### Databricks Support
 
-Spark NLP 5.5.0 has been tested and is compatible with the following runtimes:
+Spark NLP 5.5.1 has been tested and is compatible with the following runtimes:
 
 | **CPU**            | **GPU**            |
 |--------------------|--------------------|
@@ -174,7 +174,7 @@ We are compatible with older runtimes. For a full list check databricks support
 
 ### EMR Support
 
-Spark NLP 5.5.0 has been tested and is compatible with the following EMR releases:
+Spark NLP 5.5.1 has been tested and is compatible with the following EMR releases:
 
 | **EMR Release**    |
 |--------------------|
@@ -205,7 +205,7 @@ deployed to Maven central. To add any of our packages as a dependency in your ap
 from our official documentation.
 
 If you are interested, there is a simple SBT project for Spark NLP to guide you on how to use it in your
-projects [Spark NLP SBT S5.5.0r](https://github.com/maziyarpanahi/spark-nlp-starter)
+projects [Spark NLP SBT S5.5.1r](https://github.com/maziyarpanahi/spark-nlp-starter)
 
 ### Python
 
@@ -250,7 +250,7 @@ In Spark NLP we can define S3 locations to:
 
 Please check [these instructions](https://sparknlp.org/docs/en/install#s3-integration) from our official documentation.
 
-## Document5.5.0
+## Document5.5.1
 
 ### Examples
 
@@ -283,7 +283,7 @@ the Spark NLP library:
     keywords = {Spark, Natural language processing, Deep learning, Tensorflow, Cluster},
     abstract = {Spark NLP is a Natural Language Processing (NLP) library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines that can scale easily in a distributed environment. Spark NLP comes with 1100+ pretrained pipelines and models in more than 192+ languages. It supports nearly all the NLP tasks and modules that can be used seamlessly in a cluster. Downloaded more than 2.7 million times and experiencing 9x growth since January 2020, Spark NLP is used by 54% of healthcare organizations as the world’s most widely used NLP library in the enterprise.}
     }
-}5.5.0
+}5.5.1
 ```
 
 ## Community support

build.sbt

@@ -6,7 +6,7 @@ name := getPackageName(is_silicon, is_gpu, is_aarch64)
 
 organization := "com.johnsnowlabs.nlp"
 
-version := "5.5.0"
+version := "5.5.1"
 
 (ThisBuild / scalaVersion) := scalaVer
 
@@ -185,8 +185,8 @@ val llamaCppDependencies =
     Seq(llamaCppGPU)
   else if (is_silicon.equals("true"))
     Seq(llamaCppSilicon)
-//  else if (is_aarch64.equals("true"))
-//    Seq(openVinoCPU)
+  else if (is_aarch64.equals("true"))
+    Seq(llamaCppAarch64)
   else
     Seq(llamaCppCPU)
 

conda/meta.yaml

@@ -1,13 +1,13 @@
 {% set name = "spark-nlp" %}
-{% set version = "5.5.0" %}
+{% set version = "5.5.1" %}
 
 package:
   name: {{ name|lower }}
   version: {{ version }}
 
 source:
   url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/spark-nlp-{{ version }}.tar.gz
-  sha256: edc71585f462f548770bd13899686f10d88fa4a4a6e201bc1bf9c7711e398dc0
+  sha256: e8ddaf939a1b0acbe0d7b6d6a67f7fa0c5a73339d9e4563e3c1aba1cf0039409
 
 build:
   noarch: python

docs/_data/navigation.yml

@@ -44,6 +44,8 @@ sparknlp:
         url: /docs/en/pipelines
       - title: General Concepts
         url: /docs/en/concepts
+      - title: Tasks
+        url: /docs/en/tasks/landing_page
       - title: Annotators
         url: /docs/en/annotators
       - title: Transformers

docs/_layouts/landing.html

@@ -201,7 +201,7 @@ <h3 class="grey h3_title">{{ _section.title }}</h3>
                   <div class="highlight-box">
     {% highlight bash %}
     # Using PyPI
-    $ pip install spark-nlp==5.5.0
+    $ pip install spark-nlp==5.5.1
 
     # Using Anaconda/Conda
     $ conda install -c johnsnowlabs spark-nlp

docs/api/com/index.html

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-          <meta name="description" content="Spark NLP 5.5.0 ScalaDoc - com" />
-          <meta name="keywords" content="Spark NLP 5.5.0 ScalaDoc com" />
+          <title>Spark NLP 5.5.1 ScalaDoc  - com</title>
+          <meta name="description" content="Spark NLP 5.5.1 ScalaDoc - com" />
+          <meta name="keywords" content="Spark NLP 5.5.1 ScalaDoc com" />
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docs/api/com/johnsnowlabs/client/CloudClient.html

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-          <meta name="keywords" content="Spark NLP 5.5.0 ScalaDoc com.johnsnowlabs.client.CloudClient" />
+          <title>Spark NLP 5.5.1 ScalaDoc  - com.johnsnowlabs.client.CloudClient</title>
+          <meta name="description" content="Spark NLP 5.5.1 ScalaDoc - com.johnsnowlabs.client.CloudClient" />
+          <meta name="keywords" content="Spark NLP 5.5.1 ScalaDoc com.johnsnowlabs.client.CloudClient" />
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docs/api/com/johnsnowlabs/client/CloudManager.html

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+          <title>Spark NLP 5.5.1 ScalaDoc  - com.johnsnowlabs.client.CloudManager</title>
+          <meta name="description" content="Spark NLP 5.5.1 ScalaDoc - com.johnsnowlabs.client.CloudManager" />
+          <meta name="keywords" content="Spark NLP 5.5.1 ScalaDoc com.johnsnowlabs.client.CloudManager" />
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-        <span id="doc-title">Spark NLP 5.5.0 ScalaDoc<span id="doc-version"></span></span>
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docs/api/com/johnsnowlabs/client/CloudResources$.html

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+          <meta name="description" content="Spark NLP 5.5.1 ScalaDoc - com.johnsnowlabs.client.CloudResources" />
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docs/api/com/johnsnowlabs/client/CloudStorage.html

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+          <meta name="description" content="Spark NLP 5.5.1 ScalaDoc - com.johnsnowlabs.client.CloudStorage" />
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docs/api/com/johnsnowlabs/client/aws/AWSAnonymousCredentials.html

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-          <meta name="keywords" content="Spark NLP 5.5.0 ScalaDoc com.johnsnowlabs.client.aws.AWSAnonymousCredentials" />
+          <title>Spark NLP 5.5.1 ScalaDoc  - com.johnsnowlabs.client.aws.AWSAnonymousCredentials</title>
+          <meta name="description" content="Spark NLP 5.5.1 ScalaDoc - com.johnsnowlabs.client.aws.AWSAnonymousCredentials" />
+          <meta name="keywords" content="Spark NLP 5.5.1 ScalaDoc com.johnsnowlabs.client.aws.AWSAnonymousCredentials" />
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docs/api/com/johnsnowlabs/client/aws/AWSBasicCredentials.html

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+          <title>Spark NLP 5.5.1 ScalaDoc  - com.johnsnowlabs.client.aws.AWSBasicCredentials</title>
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docs/api/com/johnsnowlabs/client/aws/AWSClient.html

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-          <meta name="keywords" content="Spark NLP 5.5.0 ScalaDoc com.johnsnowlabs.client.aws.AWSClient" />
+          <title>Spark NLP 5.5.1 ScalaDoc  - com.johnsnowlabs.client.aws.AWSClient</title>
+          <meta name="description" content="Spark NLP 5.5.1 ScalaDoc - com.johnsnowlabs.client.aws.AWSClient" />
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+          <title>Spark NLP 5.5.1 ScalaDoc  - com.johnsnowlabs.client.aws.AWSCredentialsProvider</title>
+          <meta name="description" content="Spark NLP 5.5.1 ScalaDoc - com.johnsnowlabs.client.aws.AWSCredentialsProvider" />
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+          <meta name="description" content="Spark NLP 5.5.1 ScalaDoc - com.johnsnowlabs.client.aws.AWSGateway" />
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