This package features data-science related tasks for developing new recognizers for Presidio. It is used for the evaluation of the entire system, as well as for evaluating specific PII recognizers or PII detection models.
machine-learning
deep-learning
nlp
natural-language-processing
privacy
ner
transformers
pii
named-entity-recognition
spacy
flair
Обновлено 2024-10-27 15:51:02 +03:00
Translation quality evaluation for Firefox Translations models
Обновлено 2023-10-24 00:14:07 +03:00
Translation quality evaluation for Firefox Translations models
Обновлено 2023-10-24 00:14:07 +03:00
Table Transformer (TATR) is a deep learning model for extracting tables from unstructured documents (PDFs and images). This is also the official repository for the PubTables-1M dataset and GriTS evaluation metric.
Обновлено 2023-09-07 07:38:34 +03:00
A library & tools to evaluate predictive language models.
nlp
language-model
evaluation
evaluation-toolkit
language-model-evaluation
lm-challenge
next-word-prediction
ngram-model
prediction-model
research-tool
Обновлено 2023-08-09 18:22:29 +03:00
Record-and-replay tools are indispensable for quality assurance of mobile applications. However, by conducting an empirical study of various existing tools in industrial settings, researchers have concluded that no existing tools under evaluation are sufficient for industrial applications. In this project, we present a record-and-replay tool called SARA towards bridging the gap and targeting a wide adoption.
Обновлено 2023-06-12 21:21:33 +03:00
Обновлено 2023-03-10 02:59:53 +03:00
Forecasting models, development, evaluation, and validation
Обновлено 2022-01-11 21:12:40 +03:00
FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.
Обновлено 2022-01-06 19:18:51 +03:00
A python implementation for a CNTK Fast-RCNN evaluation client
Обновлено 2017-07-04 11:22:40 +03:00