Few-Shot Prompting Task
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A Few-Shot Prompting Task is a NLP task that require an input of exemplar prompts.
- Example(s):
- Counter-Example(s):
- See: Few-Shot Learning.
Referneces
2023
- chat
- Few-shot prompting is a technique used in the context of machine learning, particularly with large-scale language models like GPT-3 and GPT-4. It involves providing a model with a few examples or instances (called "prompts") to demonstrate the desired task or format of the response. The model then generalizes from these examples to perform the task with new input data.
The idea behind few-shot prompting is that these models have already learned a lot of knowledge during their pre-training, and providing a few examples helps them understand the user's intent and adapt to a wide range of tasks without the need for extensive fine-tuning.
- Few-shot prompting is a technique used in the context of machine learning, particularly with large-scale language models like GPT-3 and GPT-4. It involves providing a model with a few examples or instances (called "prompts") to demonstrate the desired task or format of the response. The model then generalizes from these examples to perform the task with new input data.
2022
- (Wei, Tay et al., 2022) ⇒ Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus.. (2022). “Emergent Abilities of Large Language Models.” In: Transactions on Machine Learning Research, 08/2022 (TMLR).
- QUOTE: ... We survey emergent abilities as observed in a range of prior work, categorizing them in settings such as few-shot prompting (§3) and augmented prompting strategies (§4). ...