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Release/553 release candidate #14511

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Jan 30, 2025
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Release/553 release candidate #14511

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0898d8c
Fix the bug generating wrong embeddings
maziyarpanahi Jan 6, 2025
9ac93ba
fixing attention mask in bge, e5, mxbai, nomic, snowflake, and uae
maziyarpanahi Jan 6, 2025
a6a6fca
fix issue with attention mask calculation
maziyarpanahi Jan 16, 2025
d0da98d
Add a new CLSToken feature to BGE annotator [skip test]
maziyarpanahi Jan 29, 2025
aefce9b
code reformat [skip test]
maziyarpanahi Jan 29, 2025
7a9f845
LLama3 download fix (#14508)
C-K-Loan Jan 29, 2025
14daf85
Merge pull request #14496 from JohnSnowLabs/bugfix/mpnet-attentionmas…
maziyarpanahi Jan 29, 2025
69de5c2
Bump to 5.5.3 [run doc]
maziyarpanahi Jan 30, 2025
9948696
Fix duplicate docstring causing docs not to build [run doc]
maziyarpanahi Jan 30, 2025
7137acb
Update Scala and Python APIs
actions-user Jan 30, 2025
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14 changes: 14 additions & 0 deletions CHANGELOG
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========
5.5.3
========
----------------
Bug Fixes & Enhancements
----------------
* BGEEmbeddings: The default pretrained model for BGEEmbeddings has been changed from "bge_base" to "bge_small_en_v1.5". Users relying on the old default will need to explicitly specify "bge_base" in the pretrained method.
* Added useCLSToken parameter to allow users to choose between CLS token pooling and attention-based average pooling for sentence embeddings.
* BGEEmbeddings: BGEEmbeddings now supports a `useCLSToken` parameter, which defaults to True. This affects the embedding calculation strategy. Existing users should verify their usage and potentially set this parameter explicitly.
* Added HasClsTokenProperties in Scala: Introduced the HasClsTokenProperties trait in Scala providing useCLSToken parameter functionality for relevant annotators.
* Fixing wrong padding in attention mask in `MPNet`, `BGE`, `E5`, `Mxbai`, `Nomic`, `SnowFlake`, and `UAE`. This resulted in wrong inference results in some cases and not equal to the ONNX version in transformers/sentence-transformers.
* Various Performance Optimizations: Multiple changes across different models (Albert, Bart, CLIP, CamemBert, ConvNextClassifier, DeBerta, DistilBert, E5, Instructor, MPNet, Mxbai, Nomic, RoBerta, SnowFlake, UAE, ViTClassifier, VisionEncoderDecoder, Wav2Vec2, XlmRoBertaClassification, XlmRoberta) appear to focus on performance improvements and code cleanup, especially related to OpenVINO and ONNX inference. These may lead to faster inference times.
* Fixing Llama3 download issue in Python.

========
5.5.2
========
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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==5.5.2 pyspark==3.3.1
$ pip install spark-nlp==5.5.3 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 *5.5.2* 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 *5.5.3* 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 5.5.2 has been tested and is compatible with the following runtimes:
Spark NLP 5.5.3 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 5.5.2 has been tested and is compatible with the following EMR releases:
Spark NLP 5.5.3 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 S5.5.2r](https://github.com/maziyarpanahi/spark-nlp-starter)
projects [Spark NLP SBT S5.5.3r](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.

## Document5.5.2
## Document5.5.3

### 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.}
}
}5.5.2
}5.5.3
```

## Community support
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2 changes: 1 addition & 1 deletion 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 := "5.5.2"
version := "5.5.3"

(ThisBuild / scalaVersion) := scalaVer

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2 changes: 1 addition & 1 deletion conda/meta.yaml
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{% set name = "spark-nlp" %}
{% set version = "5.5.2" %}
{% set version = "5.5.3" %}

package:
name: {{ name|lower }}
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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==5.5.2
$ pip install spark-nlp==5.5.3

# Using Anaconda/Conda
$ conda install -c johnsnowlabs spark-nlp
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