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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
95.47% on CIFAR10 with PyTorch
| Date | Stars |
|---|---|
| 2026-07-30 | 6415 |
| 2026-08-10 | 6421 |
| 2026-08-18 | 6422 |
| 2026-08-19 | 6422 |
| 2026-08-21 | 6422 |
| 2026-08-22 | 6421 |
| 2026-08-23 | 6422 |
| 2026-08-24 | 6423 |
| 2026-08-27 | 6424 |
| 2026-08-30 | 6425 |
| 2026-08-31 | 6424 |
| 2026-09-01 | 6425 |
| 2026-09-02 | 6425 |
| 2026-09-03 | 6426 |
| 2026-09-04 | 6426 |
| 2026-09-05 | 6427 |
| 2026-09-07 | 6428 |
| 2026-09-08 | 6426 |
| 2026-09-10 | 6430 |
| 2026-09-13 | 6431 |
| 2026-09-14 | 6433 |
| 2026-09-15 | 6435 |
| 2026-09-17 | 6436 |
| 2026-09-18 | 6436 |
| 2026-09-20 | 6437 |
| 2026-09-22 | 6438 |
| 2026-09-23 | 6440 |
| 2026-09-24 | 6443 |
| 2026-09-27 | 6444 |
| 2026-09-28 | 6442 |
| 2026-09-30 | 6441 |
| 2026-10-02 | 6442 |
| 2026-10-05 | 6441 |
| 2026-10-08 | 6440 |
| 2026-10-09 | 6441 |
| 2026-10-11 | 6444 |
| 2026-10-14 | 6445 |
| 2026-10-15 | 6446 |
| 2026-10-16 | 6445 |
| 2026-10-17 | 6446 |
| 2026-10-19 | 6445 |
| 2026-10-20 | 6444 |
| 2026-10-21 | 6445 |
| 2026-10-22 | 6447 |
| 2026-10-25 | 6447 |
| 2026-10-26 | 6446 |
| 2026-10-27 | 6447 |
| 2026-10-28 | 6447 |
| 2026-10-29 | 6447 |
| 2026-10-30 | 6448 |
| 2026-10-31 | 6449 |
| 2026-11-01 | 6450 |
| 2026-11-02 | 6448 |
| 2026-11-04 | 6449 |
Today
— stars today
This week
+1 stars this week
This month
+7 stars this month
Momentum
0.0
growth rate 0.02%/day
# Train CIFAR10 with PyTorch I'm playing with [PyTorch](http://pytorch.org/) on the CIFAR10 dataset. ## Prerequisites - Python 3.6+ - PyTorch 1.0+ ## Training ``` # Start training with: python main.py # You can manually resume the training with: python main.py --resume --lr=0.01 ``` ## Accuracy | Model | Acc. | | ----------------- | ----------- | | [VGG16](https://arxiv.org/abs/1409.1556) | 92.64% | | [ResNet18](https://arxiv.org/abs/1512.03385) | 93.02% | | [ResNet50](https://arxiv.org/abs/1512.03385) | 93.62% | | [ResNet101](https://arxiv.org/abs/1512.03385) | 93.75% | | [RegNetX_200MF](https://arxiv.org/abs/2003.13678) | 94.24% | | [RegNetY_400MF](https://arxiv.org/abs/2003.13678) | 94.29% | | [MobileNetV2](https://arxiv.org/abs/1801.04381) | 94.43% | | [ResNeXt29(32x4d)](https://arxiv.org/abs/1611.05431) | 94.73% | | [ResNeXt29(2x64d)](https://arxiv.org/abs/1611.05431) | 94.82% | | [SimpleDLA](https://arxiv.org/abs/1707.064) | 94.89% | | [DenseNet121](https://arxiv.org/abs/1608.06993) | 95.04% | | [PreActResNet18](https://arxiv.org/abs/1603.05027) | 95.11% | | [DPN92](https://arxiv.org/abs/1707.01629) | 95.16% | | [DLA](https://arxiv.org/pdf/1707.06484.pdf) | 95.47% |
Excerpt of 1,384 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:582366b5b4a05ad4, topic:pytorch
