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<<<domain>>>: Natural Language Processing Text Classification
<<<api_call>>>: pipeline('sentiment-analysis')
<<<api_provider>>>: Hugging Face Transformers
<<<explanation>>>: The Hugging Face Transformers library provides a high-level API called pipeline for many common tasks. In this case, we are using the 'sentiment-analysis' pipeline which is a text classification task. This pipeline will take in a string of text (in this case, the content of an article), and return a sentiment classification (either positive or negative). This can be used to recommend articles to users based on the sentiment of their previously liked articles.
<<<code>>>: 
```python
from transformers import pipeline
sentiment_analysis = pipeline('sentiment-analysis')
```
This code first imports the pipeline function from the transformers module. Then it creates a sentiment analysis pipeline. You can use this pipeline by calling `sentiment_analysis(article_text)`, where `article_text` is a string containing the text of the article. The pipeline will return a list of dictionaries, each containing a label ('POSITIVE' or 'NEGATIVE') and a score.

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gpt-4-0613