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Tips for Successfully Training Transformers on Small Datasets
It turns out that you can easily train transformers on small datasets when you use tricks (and have the patience to train a very long time).
transformers small-datasets training ptb
A Recipe for Training Neural Networks
The most common neural net mistakes and listing a few common gotchas related to training neural nets.
systems-design checklist training debugging
Data Project Checklist
There’s a lot more to creating useful data projects than just training an accurate model!
product-management databases training checklist
Customizing What Happens in Fit()
How to leverage the convenient features of fit() with a custom training loop.
tensorflow keras training tutorial
TOMA: Torch Memory-adaptive Algorithms
Helps you write algorithms in PyTorch that adapt to the available (CUDA) memory.
training cuda lstm gpu
Tpus, Systolic Arrays, and bfloat16: Accelerate Your DL
Systolic arrays and bfloat16 multipliers, two components of tensor processing units (TPUs) that are responsible for accelerating your deep learning ...
tpu bfloat16 training tutorial
AWS vs Paperspace vs FloydHub : Choosing your cloud GPU partner
A look at various features of the top three cloud GPU service providers.
distributed-training gpu aws floydhub
Training Neural Nets on Larger Batches
💥 Practical Tips for 1-GPU, Multi-GPU & Distributed setups
distributed-training training gpu convolutional-neural-networks
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