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wozeparrot e9c1ae3825 Add a quick start guide (#900 )

* feat: initial quick start guide

* fix: fix link

* feat: add note about jit

* feat: add note about load/store ops

* feat: add link to discord

* feat: add note about saving and loading models

* fix: correct code for saving and loading

* feat: overhaul docs

* fix: fix link

* feat: wording

* feat: add link to discord

* feat: contributing guidelines

* feat: make contributing section more doc focused

* feat: add link to env_vars from readme

* fix: wording

* feat: move community to bottom

* feat: showcase

* feat: linebreak

* feat: redesigned header

* feat: tweaks

* feat: tweaks

* feat: badge for lines of code

* feat: move installation instructions to repo readme

* feat: readme overhaul number 2

* feat: move visualization to quick start guide

* feat: readme 2 electric boogaloo

* fix: grammar

* fix: formatting

* feat: no ugly line

* feat: add line back

* feat: new load method

* feat: split adding accelerator docs out

* feat: showcase whisper

* feat: smaller tweaks

* feat: bring back oneliner

2023-06-04 08:51:20 -07:00

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tinygrad Showcase

Despite being a tiny library, tinygrad is capable of doing a lot of things. From state-of-the-art vision to state-of-the-art language models.

Vision

EfficientNet

You can either pass in the URL of a picture to discover what it is:

python3 examples/efficientnet.py https://media.istockphoto.com/photos/hen-picture-id831791190

Or, if you have a camera and OpenCV installed, you can detect what is in front of you:

python3 examples/efficientnet.py webcam

YOLOv3

Take a look at yolov3.py.

Audio

Whisper

Take a look at whisper.py. You need pyaudio and torchaudio installed.

SMALL=1 python3 examples/whisper.py

Generative

Generative Adversarial Networks

Take a look at mnist_gan.py.

Stable Diffusion

You will need to download the weights of Stable Diffusion and put it into the weights/ directory.

python3 examples/stable_diffusion.py

"a horse sized cat eating a bagel"

LLaMA

You will need to download and put the weights into the weights/LLaMA directory, which may need to be created.

Then you can have a chat with Stacy:

python3 examples/llama.py

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