Tiiiger/bert_score
BERT score for text generation
This tool helps you automatically assess the quality of generated text, such as summaries, translations, or chatbots' responses. It takes your generated text and a human-written reference text, then outputs scores that indicate how similar and good your generated text is. Anyone working with AI language models, like researchers or product developers, who needs to quickly evaluate text quality without relying solely on manual human review, would find this useful.
1,880 stars. Used by 18 other packages. No commits in the last 6 months. Available on PyPI.
Use this if you need an automated, robust way to measure how well your AI-generated text aligns with human-quality examples, providing precision, recall, and F1 scores.
Not ideal if your primary concern is assessing grammatical correctness, fluency, or other human-like qualities that don't directly relate to semantic similarity with a reference text.
Stars
1,880
Forks
237
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jul 30, 2024
Commits (30d)
0
Dependencies
8
Reverse dependents
18
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/Tiiiger/bert_score"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
DerwenAI/pytextrank
Python implementation of TextRank algorithms ("textgraphs") for phrase extraction
BrikerMan/Kashgari
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for...
asyml/texar
Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. ...
yohasebe/wp2txt
A command-line tool to extract plain text from Wikipedia dumps with category and section filtering
neuralmind-ai/portuguese-bert
Portuguese pre-trained BERT models