Spark NLP 5.0.2: Introducing ONNX Support for ALBERT, CmameBERT, and XLM-RoBERTa, a new Zero-Short Classifier for XLM-RoBERTa transformer, 200+ new ONNX models, and bug fixes!

[maziyarpanahi]

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📢 Overview

Spark NLP 5.0.2 🚀 comes with new ONNX support for ALBERT, CmameBERT, and XLM-RoBERTa annotators, a new Zero-Short Classifier for XLM-RoBERTa transformer, 200+ new ONNX models, and bug fixes! We want to thank our community for their valuable feedback, feature requests, and contributions. Our Models Hub now contains over 18,000+ free and truly open-source models & pipelines. 🎉

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🔥 New Features

• NEW: Introducing support for ONNX Runtime in ALBERT, CamemBERT, and XLM-RoBERTa annotators. We have already converted 200+ models to ONNX format for these annotators for our community
• NEW: Implement XlmRoBertaForZeroShotClassification annotator for Zero-Shot multi-class & multi-label text classification based on XLM-RoBERTa transformer

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🐛 Bug Fixes & Enhancements

• Fix MarianTransformers annotator breaking with java.lang.ClassCastException in Python
• Fix out of 0.0/1.0 accuracy in SentenceDetectorDL and MultiClassifierDL annotators
• Fix BART issue with a low-temperature value that only occurred when there are no non-infinite logits satisfying the low temperature and top_k values
• Add missing E5Embeddings and InstructorEmbeddings annotators to annotators in Scala for easy all-in-one import

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📖 Documentation

• Import models from TF Hub & HuggingFace
• Spark NLP Notebooks
• Models Hub with new models
• Spark NLP Articles
• Spark NLP in Action
• Spark NLP Documentation
• Spark NLP Scala APIs
• Spark NLP Python APIs

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❤️ Community support

• Slack For live discussion with the Spark NLP community and the team
• GitHub Bug reports, feature requests, and contributions
• Discussions Engage with other community members, share ideas,
  and show off how you use Spark NLP!
• Medium Spark NLP articles
• JohnSnowLabs official Medium
• YouTube Spark NLP video tutorials

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Installation

Python

#PyPI

pip install spark-nlp==5.0.2

Spark Packages

spark-nlp on Apache Spark 3.0.x, 3.1.x, 3.2.x, 3.3.x, and 3.4.x (Scala 2.12):

spark-shell --packages com.johnsnowlabs.nlp:spark-nlp_2.12:5.0.2

pyspark --packages com.johnsnowlabs.nlp:spark-nlp_2.12:5.0.2

GPU

spark-shell --packages com.johnsnowlabs.nlp:spark-nlp-gpu_2.12:5.0.2

pyspark --packages com.johnsnowlabs.nlp:spark-nlp-gpu_2.12:5.0.2

Apple Silicon (M1 & M2)

spark-shell --packages com.johnsnowlabs.nlp:spark-nlp-silicon_2.12:5.0.2

pyspark --packages com.johnsnowlabs.nlp:spark-nlp-silicon_2.12:5.0.2

AArch64

spark-shell --packages com.johnsnowlabs.nlp:spark-nlp-aarch64_2.12:5.0.2

pyspark --packages com.johnsnowlabs.nlp:spark-nlp-aarch64_2.12:5.0.2

Maven

spark-nlp on Apache Spark 3.0.x, 3.1.x, 3.2.x, 3.3.x, and 3.4.x:

<dependency>
    <groupId>com.johnsnowlabs.nlp</groupId>
    <artifactId>spark-nlp_2.12</artifactId>
    <version>5.0.2</version>
</dependency>

spark-nlp-gpu:

<dependency>
    <groupId>com.johnsnowlabs.nlp</groupId>
    <artifactId>spark-nlp-gpu_2.12</artifactId>
    <version>5.0.2</version>
</dependency>

spark-nlp-silicon:

<dependency>
    <groupId>com.johnsnowlabs.nlp</groupId>
    <artifactId>spark-nlp-silicon_2.12</artifactId>
    <version>5.0.2</version>
</dependency>

spark-nlp-aarch64:

<dependency>
    <groupId>com.johnsnowlabs.nlp</groupId>
    <artifactId>spark-nlp-aarch64_2.12</artifactId>
    <version>5.0.2</version>
</dependency>

FAT JARs

• CPU on Apache Spark 3.x/3.1.x/3.2.x/3.3.x/3.4.x: https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/jars/spark-nlp-assembly-5.0.2.jar

• GPU on Apache Spark 3.0.x/3.1.x/3.2.x/3.3.x/3.4.x: https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/jars/spark-nlp-gpu-assembly-5.0.2.jar

• M1 on Apache Spark 3.0.x/3.1.x/3.2.x/3.3.x/3.4.x: https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/jars/spark-nlp-silicon-assembly-5.0.2.jar

• AArch64 on Apache Spark 3.0.x/3.1.x/3.2.x/3.3.x/3.4.x: https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/jars/spark-nlp-aarch64-assembly-5.0.2.jar

What's Changed

• SPARKNLP-738 Enforcing accuracy to 0 and 1 in classifiers by @danilojsl in SPARKNLP-738 Enforcing accuracy to 0 and 1 in classifiers #13901
• Introducing a new Zero-Short Classifier for XLM-RoBERTa transformer by @ahmedlone127 in Introducing a new Zero-Short Classifier for XLM-RoBERTa transformer #13902
• Add support for ONNX to ALBERT, CamemBERT, and XLM-RoBERTa by @maziyarpanahi in Add support for ONNX to ALBERT, CamemBERT, and XLM-RoBERTa #13907
• SPARKNLP-873 Issue with MarianTransformers models by @danilojsl in SPARKNLP-873 Issue with MarianTransformers models #13908
• BART Bug fix The summarization model(s) are not giving any result #13898 by @prabod in BART Bug fix #13898 #13911
• Models hub by @maziyarpanahi in Models hub #13913
• release/502-release-candidate by @maziyarpanahi in release/502-release-candidate #13912

Full Changelog: 5.0.1...5.0.2

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This discussion was created from the release Spark NLP 5.0.2: Introducing ONNX Support for ALBERT, CmameBERT, and XLM-RoBERTa, a new Zero-Short Classifier for XLM-RoBERTa transformer, 200+ new ONNX models, and bug fixes!.