spark-nlp
gector
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| spark-nlp | gector | |
|---|---|---|
| 87 | 2 | |
| 3,656 | 861 | |
| 0.8% | 1.2% | |
| 9.4 | 0.0 | |
| 7 days ago | 8 months ago | |
| Scala | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
spark-nlp
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PySpark for NLP Workshop - Materials and Jupyter Notebooks
I recently had the opportunity to run a workshop at ODSC East, focusing on using PySpark for Natural Language Processing (NLP). Had a great time explaining PySpark's fundamentals and exploring the Spark NLP library.
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Transformers.js
I'd like to use this transformer model in rust (because it's on the backend, because I can use data munging and it will be faster, and for other reasons). It looks like a good model! But, it doesn't compile on Apple Silicon for wierd linking issues that aren't apparent - https://github.com/guillaume-be/rust-bert/issues/338. I've spent a large part of today and yesterday attempting to find out why. The only other library that I've found for doing this kind of thing programmatically (particularly sentiment analysis) is this (https://github.com/JohnSnowLabs/spark-nlp). Some of the models look a little older, which is OK, but it does mean that I'd have to do this in another language.
Does anyone know of any sentiment analysis software that can be tuned (other than VADER - I'm looking for more along the lines of a transformer model) - like BERT, but is pretrained and can be used in Rust or Python? Otherwise I'll probably using spark-nlp and having to spin another process.
Thanks.
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Release John Snow Labs Spark-NLP 4.3.0: New HuBERT for speech recognition, new Swin Transformer for Image Classification, new Zero-shot annotator for Entity Recognition, CamemBERT for question answering, new Databricks and EMR with support for Spark 3.3, 1000+ state-of-the-art models and many more!
I saw Wav2Vec2 a couple of releases ago: https://github.com/JohnSnowLabs/spark-nlp/releases/tag/4.2.0
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Data science in Scala
I am not aware of common open frameworks like Tensorflow, PyTorch or Scikit-learn for Scala. But specifically for natural language processing, there's SparkNLP from John Snow Labs.
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Spark-NLP 4.1.0 Released: Vision Transformer (ViT) is here! The very first Computer Vision pipeline for the state-of-the-art Image Classification task, AWS Graviton/ARM64 support, new EMR & Databricks support, 1000+ state-of-the-art models, and more!
NEW: Introducing ViTForImageClassification annotator in Spark NLP 🚀. ViTForImageClassification can load Vision Transformer ViT Models with an image classification head on top (a linear layer on top of the final hidden state of the [CLS] token) e.g. for ImageNet. This annotator is compatible with all the models trained/fine-tuned by using ViTForImageClassification for PyTorch or TFViTForImageClassification for TensorFlow models in HuggingFace 🤗 (https://github.com/JohnSnowLabs/spark-nlp/pull/11536)
- Spark-NLP 4.0.0 🚀: New modern extractive Question answering (QA) annotators for ALBERT, BERT, DistilBERT, DeBERTa, RoBERTa, Longformer, and XLM-RoBERTa, official support for Apple silicon M1, support oneDNN to improve CPU up to 97%, improved transformers on GPU up to +700%, 1000+ SOTA models
- How can you do efficient text preprocessing?
- John Snow Labs Spark-NLP 3.4.0: New OpenAI GPT-2, new ALBERT, XLNet, RoBERTa, XLM-RoBERTa, and Longformer for Sequence Classification, support for Spark 3.2, new distributed Word2Vec, extend support to more Databricks & EMR runtimes, new state-of-the-art transformer models, bug fixes, and lots more!
gector
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ML application for grammar correction
If you capture it, you might as well correct it. Check out Gramformer or Grammarly's Gector. You can do scoring based on number of mistakes proposed by these models i.e. the fewer, the better.
- Is there any way to detect grammatical errors and classify text as being either grammatically correct/incorrect?
What are some alternatives?
Gramformer - A framework for detecting, highlighting and correcting grammatical errors on natural language text. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
nlu - 1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
clj-djl - clojure wrap for deep java library(DJL.ai)
Tribuo - Tribuo - A Java machine learning library
libpython-clj - Python bindings for Clojure
DeBERTa - The implementation of DeBERTa
cobrix - A COBOL parser and Mainframe/EBCDIC data source for Apache Spark
spark-nlp-display - A library for the simple visualization of different types of Spark NLP annotations.