Editing Nlp (section)

== <span style="color: #FFFFFF;">Applying</span> ==
'''Text classification with a pre-trained transformer (HuggingFace):'''

<syntaxhighlight lang="python">
from transformers import pipeline

# Sentiment analysis using a pre-trained model
classifier = pipeline("sentiment-analysis",
                       model="distilbert-base-uncased-finetuned-sst-2-english")

results = classifier([
    "This film was absolutely wonderful!",
    "The service was terrible and I want a refund."
])
# [{'label': 'POSITIVE', 'score': 0.9998}, {'label': 'NEGATIVE', 'score': 0.9996}]

# Named Entity Recognition
ner = pipeline("ner", grouped_entities=True)
ner("Apple was founded by Steve Jobs in Cupertino, California.")
# [{'entity_group': 'ORG', 'word': 'Apple', ...},
#  {'entity_group': 'PER', 'word': 'Steve Jobs', ...},
#  {'entity_group': 'LOC', 'word': 'Cupertino, California', ...}]
</syntaxhighlight>

; Common NLP task → model mapping
: '''Text classification''' → BERT fine-tuned, DistilBERT, RoBERTa
: '''Text generation''' → GPT-2/3/4, LLaMA, Mistral
: '''Translation''' → MarianMT, NLLB, Google Translate API
: '''Summarization''' → BART, Pegasus, T5
: '''Question answering''' → RoBERTa fine-tuned on SQuAD
: '''Semantic search''' → Sentence-BERT, E5, text-embedding-ada-002
</div>

<div style="background-color: #8B4500; color: #FFFFFF; padding: 20px; border-radius: 8px; margin-bottom: 15px;">