gector
spark-nlp
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| gector | spark-nlp | |
|---|---|---|
| 2 | 87 | |
| 863 | 3,667 | |
| 1.4% | 1.1% | |
| 0.0 | 9.4 | |
| 9 months ago | 6 days ago | |
| Python | Scala | |
| Apache License 2.0 | Apache License 2.0 |
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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?
spark-nlp
- Spark NLP 5.1.0: Introducing state-of-the-art OpenAI Whisper speech-to-text, OpenAI Embeddings and Completion transformers, MPNet text embeddings, ONNX support for E5 text embeddings, new multi-lingual BART Zero-Shot text classification, and much more!
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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.
- Spark-NLP 4.4.0: New BART for Text Translation & Summarization, new ConvNeXT Transformer for Image Classification, new Zero-Shot Text Classification by BERT, more than 4000+ state-of-the-art models, and many more! · JohnSnowLabs/spark-nlp
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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.
- 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!
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
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
DeBERTa - The implementation of DeBERTa
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.
happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
clj-djl - clojure wrap for deep java library(DJL.ai)
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
Tribuo - Tribuo - A Java machine learning library