Find agent skills by outcome

Contributing

This project welcomes contributions and suggestions. Most contributions require you to

Copyright (c) Microsoft Corporation.

repos:

Microsoft Open Source Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct.

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Microsoft takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organizations, which include Microsoft, Azure, DotN...

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TaskWeaver

autoeval/evaluatorconfig.json

!sample/*.csv

*.sh text eol=lf

generic skill

TODO: The maintainer of this repo has not yet edited this file

REPO OWNER: Do you want Customer Service & Support (CSS) support for this product/project?

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Microsoft takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organizations, which include Microsoft, Azure, DotN...

JARVIS

ALL

*.dev.yaml

Microsoft Open Source Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct.

To contribute to this GitHub project, you can follow these steps:

1. Fork the repository you want to contribute to by clicking the "Fork" button on the project page.

Build a Large Language Model (From Scratch)

This repository contains the code for developing, pretraining, and finetuning a GPT-like LLM and is the official code repository for the book Build a Large Language Model (From Scratch).

Reports

reports/

[submodule "reasoning-from-scratch"]

path = reasoning-from-scratch

.DS_Store

.idea

nanoGPT

!nanoGPT

Override jupyter in Github language stats for more accurate estimate of repo code languages

*.ipynb linguist-generated

llm.c

LLMs in simple, pure C/CUDA with no need for 245MB of PyTorch or 107MB of cPython. Current focus is on pretraining, in particular reproducing the GPT-2 and GPT-3 miniseries, along with a parallel PyTo...

dot files and such

.vscode

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LLMSurvey

A collection of papers and resources related to Large Language Models.

The Practical Guides for Large Language Models