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Sparknlp 1060 implement phi 3.5 vision #14444

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7adf658
[SPARKNLP-1068] Introducing BLIPForQuestionAnswering transformer
danilojsl Oct 2, 2024
af0c319
[SPARKNLP-1068] Adding BLIPForQuestionAnswering import notebook example
danilojsl Oct 2, 2024
c256e16
[SPARKNLP-1068] Fix fullAnnotateImage validation
danilojsl Oct 3, 2024
7c46662
[SPARKNLP-1068] Solves BLIPForQuestionAnsweringTest issue
danilojsl Oct 3, 2024
1b4b29d
[SPARKNLP-1068] Updates default BLIPForQuestionAnswering model name
danilojsl Oct 4, 2024
e121763
[SPARKNLP-1068] [skip test] Adding documentation to BLIPForQuestionAn…
danilojsl Oct 9, 2024
317abf9
Add a new llama_cpp engine (#14436)
maziyarpanahi Oct 18, 2024
4be100e
tasks-docs-integration (#14428)
AbdullahMubeenAnwar Oct 18, 2024
11a7fd9
Introducing BertForMultipleChoice transformer (#14435)
danilojsl Oct 18, 2024
12c1014
fixing the missing import
maziyarpanahi Oct 18, 2024
93f383e
Fix pretrained models not being found on dbfs systems (#14438)
DevinTDHa Oct 21, 2024
cea9cf5
[SPARKNLP-1067] PromptAssembler (#14439)
DevinTDHa Oct 21, 2024
93e029d
[SPARKNLP-1084] Adding notebooks for BertForMultipleChoice
danilojsl Oct 21, 2024
fcfdcd6
name llama_cpp to llamacpp engine
maziyarpanahi Oct 24, 2024
2f778ed
add a default engine to the AutoGGUFModel
maziyarpanahi Oct 24, 2024
2e4e354
Bump to 5.5.1 and update CHANGELOG [run doc]
maziyarpanahi Oct 24, 2024
b2e429f
Update Scala and Python APIs
actions-user Oct 24, 2024
21647e5
release conda 5.5.1 [skip test]
maziyarpanahi Oct 24, 2024
0f3e657
Fix tasks path in navigation
maziyarpanahi Oct 24, 2024
3c5994e
Phi3V preprocessing utils
prabod Sep 19, 2024
737b1b0
added phi3v
prabod Oct 23, 2024
67bc194
add phi3v scala API
prabod Oct 28, 2024
f2e3480
Added tests
prabod Oct 29, 2024
25580a9
Phi3V python api and tests
prabod Oct 29, 2024
3a9cae6
added byte fallback
prabod Oct 29, 2024
0bb77b9
changed to pretrained
prabod Oct 29, 2024
bfaf0ec
export notebook
prabod Oct 30, 2024
f7e6d2d
updated testes
prabod Oct 30, 2024
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33 changes: 33 additions & 0 deletions CHANGELOG
Original file line number Diff line number Diff line change
@@ -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
========
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14 changes: 7 additions & 7 deletions README.md
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Expand Up @@ -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:
Expand Down Expand Up @@ -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 |
|-----------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|
Expand Down Expand Up @@ -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** |
|--------------------|--------------------|
Expand All @@ -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** |
|--------------------|
Expand Down Expand Up @@ -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

Expand Down Expand Up @@ -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

Expand Down Expand Up @@ -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
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6 changes: 3 additions & 3 deletions build.sbt
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Expand Up @@ -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

Expand Down Expand Up @@ -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)

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4 changes: 2 additions & 2 deletions conda/meta.yaml
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@@ -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
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2 changes: 2 additions & 0 deletions docs/_data/navigation.yml
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Expand Up @@ -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
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Expand Up @@ -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
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Expand All @@ -28,7 +28,7 @@
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Expand Up @@ -3,9 +3,9 @@
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Expand All @@ -28,7 +28,7 @@
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<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
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