CONNECTED THINKING
Knowledge atlas
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1 people · 1 sources · 1 viewpoints
IN CONTEXT
fine-tuning cost efficiency
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Fine-tuning cost: $17 for 38,340 examples
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Fine-tuning cost: $17 for 38,340 examples
Using only 38,340 examples keeps fine-tuning costs low—approximately $17.0—while larger datasets increase both cost and training time.
These are individual perspectives, not a measure of consensus. Source material stays in its original language.
Supporting evidence
How to train your own Jev for $17
Original excerpt
We only use 38,340 examples to keep our fine-tuning costs low. Training against a dataset of this size will only cost about $17.0, while larger datasets are more expensive and time-consuming to train against.
Publication dates describe the sources, not changes in belief.