labteral/ernie
Simple State-of-the-Art BERT-Based Sentence Classification with Keras / TensorFlow 2. Built with HuggingFace's Transformers.
This tool helps data scientists and machine learning engineers categorize text data quickly and accurately. You provide it with text examples labeled with categories (like positive/negative sentiment, or topic labels), and it trains a model. The output is a highly accurate system that can predict the category of new, unseen text passages.
201 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to build a robust system for classifying sentences or short texts based on custom categories using state-of-the-art AI models.
Not ideal if you are looking for a pre-trained model to use off-the-shelf without any custom training or if your text data consists of very long documents rather than sentences.
Stars
201
Forks
30
Language
Python
License
Apache-2.0
Category
Last pushed
May 26, 2024
Commits (30d)
0
Dependencies
5
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/labteral/ernie"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
luismond/tm2tb
Bilingual term extractor
MIRICMILAN/US-AI-Patents
Code and Data for Text Classification of AI Related Patents Research Paper
AdirthaBorgohain/BERT-Text-Analysis
Text Analysis done on a business text dataset using KeyBERT and BERTopic
simonescevaroli/yelp-rating-prediction
This is the repository for the Natural Language Processing project done at Politecnico di Milano.
anisderoual/Document_Archiver_Korean-NLP_BERTClustering
📂 Extract, embed, cluster, and securely store Korean text from documents using BERT, enhancing...