All glossary terms
techniquesintermediate
Transfer Learning in NLP
Adapting pre-trained language models to specific NLP tasks by fine-tuning.
In more detail
Pre-trained models (BERT, GPT, T5) learned general language knowledge. Fine-tuning on task data adapts them efficiently. Enables good performance with limited data. Fundamental approach in modern NLP.
Examples
- BERT for text classification
- GPT-2 fine-tuning for domain text
- T5 for summarization
- Domain-specific language model adaptation
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