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.
Обновлено 2024-11-22 01:17:04 +03:00
Microsoft.Recognizers.Text provides recognition and resolution of numbers, units, date/time, etc. in multiple languages (ZH, EN, FR, ES, PT, DE, IT, TR, HI, NL. Partial support for JA, KO, AR, SV). Packages available at: https://www.nuget.org/profiles/Recognizers.Text, https://www.npmjs.com/~recognizers.text
Обновлено 2024-11-21 13:26:37 +03:00
Tutel MoE: An Optimized Mixture-of-Experts Implementation
Обновлено 2024-11-18 06:00:53 +03:00
12 Weeks, 24 Lessons, AI for All!
Обновлено 2024-11-11 22:55:47 +03:00
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Обновлено 2024-11-09 13:45:59 +03:00
Hierarchical Transformers for Knowledge Graph Embeddings (EMNLP 2021)
Обновлено 2024-07-25 14:00:19 +03:00
Knowledge Extraction For Forms Accelerators & Examples
Обновлено 2024-07-09 20:31:09 +03:00
GLUE is a lightweight, Python-based collection of scripts to support you at succeeding with speech and text use-cases based on Microsoft Azure Cognitive Services.
Обновлено 2024-06-18 03:26:03 +03:00
Code to reproduce experiments in the paper "Constrained Language Models Yield Few-Shot Semantic Parsers" (EMNLP 2021).
Обновлено 2024-05-31 20:48:22 +03:00
A benchmark for code-switched NLP, ACL 2020
Обновлено 2024-05-23 20:25:01 +03:00
This repository contains code and datasets related to entity/knowledge papers from the VERT (Versatile Entity Recognition & disambiguation Toolkit) project, by the Knowledge Computing group at Microsoft Research Asia (MSRA).
Обновлено 2024-03-16 09:53:11 +03:00
A web app to create and browse text visualizations for automated customer listening.
Обновлено 2023-10-27 06:29:49 +03:00
Firefox Translations is a webextension that enables client side translations for web browsers.
Обновлено 2023-09-04 12:30:18 +03:00
With AutoBrewML Framework the time it takes to get production-ready ML models with great ease and efficiency highly accelerates.
Обновлено 2023-08-03 09:43:02 +03:00
Self-training with Weak Supervision (NAACL 2021)
Обновлено 2023-07-25 01:35:52 +03:00
Source code for EMNLP2019 paper "Leveraging Adjective-Noun Phrasing Knowledge for Comparison Relation Prediction in Text-to-SQL".
Обновлено 2023-07-22 19:54:50 +03:00
The code of EMNLP 2019 paper "A Split-and-Recombine Approach for Follow-up Query Analysis"
Обновлено 2023-07-20 15:42:43 +03:00
Scripts to parse arxiv documents for NLP tasks
Обновлено 2023-06-12 22:03:00 +03:00
End-to-End recipes for pre-training and fine-tuning BERT using Azure Machine Learning Service
Обновлено 2023-06-12 21:59:00 +03:00
Testing Diverse Reasoning of NLI Systems
Обновлено 2022-11-28 22:08:09 +03:00
AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems
Обновлено 2022-08-19 10:21:28 +03:00
Ramp up your custom natural language processing (NLP) task, allowing you to bring your own data, use your preferred frameworks and bring models into production.
Обновлено 2022-01-10 02:07:54 +03:00
Japanese NLP sample codes
Обновлено 2021-10-19 17:45:33 +03:00
A relation-aware semantic parsing model from English to SQL
Обновлено 2021-06-19 03:42:00 +03:00
EMNLP 2020: "Dialogue Response Ranking Training with Large-Scale Human Feedback Data"
Обновлено 2021-01-22 11:17:14 +03:00