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"content": "Thanks for replying 🙏 \n\nSure .. grifters gonna grift ... and if you're playing rug-pull games with over-hyped investments expect to get, unfortunately, rug ... pulled. Defo not a clown-world defender and agree that an aspect like that is a horrible hoax with undeserving victims.\n\nBut ... What are the other soultions before LLMs? ... If you program, what tools could I use in a method that takes (text, required_key_value_extracted_pairs) and returns a JSON {\"key_1\": \"value_1\", ...} object? Advanced LLMs, with guidance, really excel in that functionality. After all, they're just heavily trained neural networks ..\n\nIn particular, I have a \"chat extract\" method in my FOSS API, https://ajrlewis.com/api/docs, that uses a HuggingFace interference model (probs LLama, can't remember lol!) to do this task ... Would love to know a different approach if you can suggest one 😊 Defo save on the overheads + complexity if I didn't want to use a 3rd party (HuggingFace) in future ...",
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