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beautiful_mnist.py link

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George Hotz
2023-11-23 14:58:22 -08:00
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@@ -48,8 +48,6 @@ And we can change `DEBUG` to `4` to see the generated code.
As it turns out, 90% of what you need for neural networks are a decent autograd/tensor library.
Throw in an optimizer, a data loader, and some compute, and you have all you need.
#### Neural network example (see examples/beautiful_mnist.py for the full thing)
```py
from tinygrad import Tensor, nn
@@ -72,6 +70,8 @@ for i in range(10):
print(i, loss.item())
```
See [examples/beautiful_mnist.py](examples/beautiful_mnist.py) for the full version that gets 98% in ~5 seconds
## Accelerators
tinygrad already supports numerous accelerators, including: