tpu
efficientnet-lite-keras
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| tpu | efficientnet-lite-keras | |
|---|---|---|
| 5 | 1 | |
| 5,179 | 38 | |
| 0.1% | - | |
| 6.3 | 0.0 | |
| 10 days ago | about 1 year ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | Apache License 2.0 |
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tpu
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Variance in reported results on ImageNet between papers [D]
Found relevant code at https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet + all code implementations here
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[D] What is the smallest, most capable, generative language model available now?
I'm looking for a generative-LM equivalent of an EfficientNet-Lite, for inference on devices with limited to no VRAM. I know about some popular ones like DistilGPT2. But it's been 2 years after its release. Surely, someone improved their size/performance ratio, right... right?
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Open source - that means free to use commercially right? ... right?
tensorflow/TPU 'apache' license - https://github.com/tensorflow/tpu/commit/6b3236d0271d2f2c3b2dfdc9d233ff00c4ba21cd
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[P] EfficientNet-lite in Keras (functional API).
According to original repository, the lite variants:
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Why do some architectures use no bias?
I was quite surprised to see that some architectures, like efficient net (official implementation: https://github.com/tensorflow/tpu/blob/master/models/official/efficientnet/efficientnet_model.py) don't use bias (bias=False). Does anyone know why is that? Apart from the obvious benefit of reducing parameters, doesn't it make the network less capable of learning certain representations?
efficientnet-lite-keras
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[P] EfficientNet-lite in Keras (functional API).
Github Link
What are some alternatives?
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