https://cdn-uploads.huggingface.co/production/uploads/69cf3431b7bee398052ee9be/ygEqMJnI9vw62-8JNuEG2.mp4
---
language:
- en
license: mit
tags:
- image-classification
- pytorch
- vgg
- benchmark
datasets:
- cifar10
metrics:
- accuracy
---
# CIFAR-10 Fast Training Benchmark (VGG-style)
This model was trained as a performance showcase for **Epochly**, a zero-config cloud GPU infrastructure.
## 🚀 Performance Results
* **Training Time:** 10.19 seconds (3 epochs)
* **Hardware:** NVIDIA Blackwell GB10 (128GB Unified Memory)
* **Setup Time:** ~10 seconds (Cold Start)
* **Framework:** PyTorch 2.5+
## 🛠️ Model Architecture
A custom **SimpleVGG** implementation with:
- 3 Convolutional blocks (64, 128, and 256 filters)
- ReLU activations and MaxPool layers
- Fully connected classifier with Dropout
- Optimized for Blackwell's FP4/FP8 tensor cores
## 📦 How to reproduce
You can find the training script `AI training.py` in the files of this repository.
To run this exact benchmark in under 10…
