Thanks, that's a great example "Panza produces a fine-tuned LLM that matches your writing style, pairing it with a Retrieval-Augmented Generation (RAG) component which helps it produce relevant emails." So fine-tuning for writing style, RAG for knowledge
PROMPT ENGINEERING
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Input vs Output Token Pricing for LLMs
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Are those prices for input or output tokens? I think they're for output tokens, but usually I find the input tokens price is more relevant – especially since most models with long context have a much lower cap on output tokens (eg Claude 3 allows 200k input but only 4k output)
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RAG vs Fine-tuning: Understanding AI Model Enhancement Techniques
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"Continue will use similarity search to automatically find important sections when answering your question" sounds like an implementation of RAG, not fine-tuning
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Demo Access for Monthly Updated LoRA Models Available?
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Is there a demo anywhere where I can talk to one of these models that's had a "monthly update" LoRA and see the working end result?
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Deep Understanding of Fine-tuning in AI Models
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Same here The best I've seen are loose explanations that fine-tuning is better for setting things like the tone of the response or teaching the model new styles of output – or helping with problems like questions-to-SQL I want deeper understanding than that
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Fine-tuning vs RAG: Adding Knowledge to Language Models
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The question here is about whether you can use fine-tuning to add small amounts of additional knowledge to an LLM – to solve the "chat about information in this documentation" problem RAG is the common solution to that problem. Can fine-tuning solve that problem too?
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Fine-tuning Models: Can It Really Add New Knowledge?
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This is why I want to see an example – just one – of a successful fine-tune that added specific extra knowledge to a model Until I've seen that I can't say for certain that it can be done
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RAG vs Fine-tuned Models: Understanding the Key Differences
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That looks like RAG or Q&A against a prompt context, not a custom fine-tuned model
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RAG and Tool Usage for Business AI Customization
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"Tailor Al to your business needs without an expensive custom model, using prompt templates and copilot actions that securely reference your business data" – sounds like that's RAG + tool usage, not a fine-tuned model
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Targeted AI Systems Answering Documentation Questions Efficiently
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By "targeted" I mean something like "answer questions about this documentation" – the kind of thing you might alternatively use RAG for