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I use them for classification, entity extraction and embeddings. I also use them as a really light UI for tasks where I don't need the capabilities of GPT3.5/4 which is overkill for the more traditional NLP tasks.

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Interesting. Could you share some detailed examples? What sort of classification? What are examples of traditional NLP tasks?

I would say anything from text classification, entity extraction, sentiment analysis, transcription, etc would be traditional NLP task, even things such as NYSIIS/Soundex processing can be handled by LLM's fairly effectively.

Huggingface categorizes their various models by task https://huggingface.co/models so it is fairly straight forward to determine what models may fit your use case.

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