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examples

Examples

This folder contains examples and best practices, written in Jupyter notebooks, for building Natural Language Processing systems for the following scenarios.

Category Applications Methods Languages
Text Classification Topic Classification BERT, XLNet, RoBERTa, DistilBERT en, hi, ar
Named Entity Recognition Wikipedia NER BERT en
Text Summarization News Summarization, Headline Generation Extractive: BERTSumExt
Abstractive: UniLM (s2s-ft)
en
Entailment MultiNLI Natural Language Inference BERT en
Question Answering SQuAD BiDAF, BERT, XLNet, DistilBERT en
Sentence Similarity STS Benchmark BERT, GenSen en
Embeddings Custom Embeddings Training Word2Vec, fastText, GloVe en
Annotation Text Annotation Doccano en
Model Explainability DNN Layer Explanation DUUDNM (Guan et al.) en

Data/Telemetry

The Azure Machine Learning notebooks collect browser usage data and send it to Microsoft to help improve our products and services. Read Microsoft's privacy statement to learn more.

To opt out of tracking, a Python script under the tools folder is also provided. Executing the script will check all notebooks under the examples folder, and automatically remove the telemetry cell:

python ../tools/remove_pixelserver.py