LM Fine-tuning AND Prompting/In-context learning
Common descendants
8 Documents
How many Labelled Examples do you need for a BERT-sized Model to Beat GPT-4 on Predictive Tasks? - Speaker Deck
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2023-10-27 About
Leandro von Werra sur X : "Companies are currently deciding whether to invest in fine-tuning their own open LLMs (e.g. Llama 2) or to use closed LLMs via an API (e.g. Claude or GPT4)..."
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2023-10-01 About
[2309.12307] LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
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2023-09-26 About
Why You (Probably) Don't Need to Fine-tune an LLM - Tidepool by Aquarium
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2023-08-19 About
Rachel Woods sur X : "There's a resurgence of interest in fine tuning LLMs I've yet to see a successful public use case where fine tuning > prompting. But here's where I see fine tuning *mattering*..."
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2023-08-19 About
Andrej Karpathy sur Twitter : "There's a chance that LoRA finetunes work so well that it dramatically alters the finetuning vs. retrieval + few-shot prompting power dynamic..."
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2023-04-21 About
[2205.05638] Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
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2022-12-15 About
How many data points is a prompt worth?
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2021-04-08 About