gector VS happy-transformer

Compare gector vs happy-transformer and see what are their differences.

gector

Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21) (by grammarly)
Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
gector happy-transformer
2 1
857 496
1.3% -
0.0 9.0
8 months ago 9 days ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

gector

Posts with mentions or reviews of gector. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-07.

happy-transformer

Posts with mentions or reviews of happy-transformer. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning happy-transformer yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing gector and happy-transformer you can also consider the following projects:

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.

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

FARM - :house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.

spark-nlp - State of the Art Natural Language Processing

transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

DeBERTa - The implementation of DeBERTa

FinBERT-QA - Financial Domain Question Answering with pre-trained BERT Language Model

small-text - Active Learning for Text Classification in Python

quickai - QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

FreeDiscovery - Web Service for E-Discovery Analytics

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.