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@ -47,6 +47,7 @@ Don't worry about training on multiple gpus or speeding up your code, lightning
- [Tutorials](https://github.com/williamFalcon/pytorch-lightning#tutorials)
- [Contributing](https://github.com/williamFalcon/pytorch-lightning#contributing)
- [Bleeding edge install](https://github.com/williamFalcon/pytorch-lightning#bleeding-edge)
- [FAQ](https://github.com/williamFalcon/pytorch-lightning#faq)
## How do I do use it?
@ -342,6 +343,22 @@ python multi_node_cluster_template.py --nb_gpu_nodes 4 --gpus '0,1,2,3,4,5,6,7'
- [9 key speed features in Pytorch-Lightning](https://towardsdatascience.com/9-tips-for-training-lightning-fast-neural-networks-in-pytorch-8e63a502f565)
- [SLURM, multi-node training with Lightning](https://towardsdatascience.com/trivial-multi-node-training-with-pytorch-lightning-ff75dfb809bd)
## FAQ
**Why was Lightning created?**
Lightning has 3 goals in mind:
1. Maximal flexibility while abstracting out the common boilerplate across research projects.
2. Reproducibility. If all projects use the LightningModule template, it will be much much easier to understand what's going on and where to look! It will also mean every implementation follows a standard format.
3. Democratizing PyTorch power user features. Distributed training? 16-bit? know you need them but don't want to take the time to implement? All good... these come built into Lightning.
**How does Lightning compare with Ignite and fast.ai?**
[Here's a thorough comparison](https://medium.com/@_willfalcon/pytorch-lightning-vs-pytorch-ignite-vs-fast-ai-61dc7480ad8a).
**Is this another library I have to learn?**
Nope! We use pure Pytorch everywhere and don't add unecessary abstractions!
**Are there plans to support Python 2?**
Nope.
## Contributing
Welcome to the PTL community! We're building the most advanced research platform on the planet to implement the latest, best practices that the amazing PyTorch team rolls out!