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* start mkdocs * simple docs for tensor * more docs * move those back * more docs * copy markdown extensions * docs legacy * docs building workflow * fix showcase links * only that? * install tinygrad * add docs to setup.py * Delete examples/llm.c/data
60 lines
1.4 KiB
Markdown
60 lines
1.4 KiB
Markdown
# tinygrad Showcase
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Despite being a tiny library, tinygrad is capable of doing a lot of things. From state-of-the-art [vision](https://arxiv.org/abs/1905.11946) to state-of-the-art [language](https://arxiv.org/abs/1706.03762) models.
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## Vision
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### EfficientNet
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You can either pass in the URL of a picture to discover what it is:
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```sh
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python3 examples/efficientnet.py ./test/models/efficientnet/Chicken.jpg
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```
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Or, if you have a camera and OpenCV installed, you can detect what is in front of you:
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```sh
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python3 examples/efficientnet.py webcam
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```
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### YOLOv8
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Take a look at [yolov8.py](/examples/yolov8.py).
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## Audio
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### Whisper
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Take a look at [whisper.py](/examples/whisper.py). You need pyaudio and torchaudio installed.
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```sh
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SMALL=1 python3 examples/whisper.py
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```
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## Generative
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### Generative Adversarial Networks
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Take a look at [mnist_gan.py](/examples/mnist_gan.py).
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### Stable Diffusion
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```sh
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python3 examples/stable_diffusion.py
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```
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*"a horse sized cat eating a bagel"*
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### LLaMA
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You will need to download and put the weights into the `weights/LLaMA` directory, which may need to be created.
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Then you can have a chat with Stacy:
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```sh
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python3 examples/llama.py
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```
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