From 21f94433b2cb6f221044ffc3bc66e4424306f438 Mon Sep 17 00:00:00 2001 From: Elvis Saravia Date: Sat, 18 Feb 2023 10:40:32 -0600 Subject: [PATCH] more notes --- guides/prompt-miscellaneous.md | 6 +++++- notebooks/pe-lecture.ipynb | 11 ++++++----- 2 files changed, 11 insertions(+), 6 deletions(-) diff --git a/guides/prompt-miscellaneous.md b/guides/prompt-miscellaneous.md index 66c4ada..9a93d6b 100644 --- a/guides/prompt-miscellaneous.md +++ b/guides/prompt-miscellaneous.md @@ -4,12 +4,16 @@ In this section, we discuss other miscellaneous but important topics in prompt e **Note that this section is under construction.** +## Program-Aided Language Models +[Gao et al., (2023)](https://arxiv.org/abs/2211.10435) presents a method that uses LLMs to read natural language problems and generate programs as the intermediate reasoning steps. Coined, program-aided language models (PAL), it differs from chain-of-thought prompting in that instead of using free-form text to obtain solution it offloads the solution step to a programmatic runtime such as a Python interpreter. + +Full example coming soon! --- ## Multimodal Prompting In this section, we will cover some examples of multimodal prompting techniques and applications that leverage multiple modalities as opposed to just text alone. -More coming soon! +Examples coming soon! --- ## GraphPrompts diff --git a/notebooks/pe-lecture.ipynb b/notebooks/pe-lecture.ipynb index fedb4ce..62edf00 100644 --- a/notebooks/pe-lecture.ipynb +++ b/notebooks/pe-lecture.ipynb @@ -46,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -55,7 +55,7 @@ "True" ] }, - "execution_count": 1, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -64,6 +64,7 @@ "import openai\n", "import os\n", "import IPython\n", + "from langchain.llms import OpenAI\n", "from dotenv import load_dotenv\n", "load_dotenv()" ] @@ -541,7 +542,7 @@ ], "metadata": { "kernelspec": { - "display_name": "minprompts", + "display_name": "promptlecture", "language": "python", "name": "python3" }, @@ -555,12 +556,12 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.15" + "version": "3.9.16" }, "orig_nbformat": 4, "vscode": { "interpreter": { - "hash": "872fbaa170678d9803e866eb8aab13838cd416716b835df572a04d4d73e81a04" + "hash": "f38e0373277d6f71ee44ee8fea5f1d408ad6999fda15d538a69a99a1665a839d" } } },