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@@ -9,7 +9,7 @@ Distributed training of large neural networks across volunteer computers.
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**[WIP]** - this branch is a work in progress. If you're interested in
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**[WIP]** - this branch is a work in progress. If you're interested in
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supplementary code for [Learning@home paper](https://arxiv.org/abs/2002.04013),
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supplementary code for [Learning@home paper](https://arxiv.org/abs/2002.04013),
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-you can find it at https://github.com/mryab/learning-at-home .
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+you can find it at https://github.com/mryab/learning-at-home.
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## What do I need to run it?
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## What do I need to run it?
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@@ -61,4 +61,4 @@ do something complex with it, please contact us by opening an issue (less prefer
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* You can achieve 4x less network load by passing quantized uint8 activations across experts.
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* You can achieve 4x less network load by passing quantized uint8 activations across experts.
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Implement your own quantization or wait for tesseract v0.8.
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Implement your own quantization or wait for tesseract v0.8.
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* Currently runtime can form batches that exceed maximal batch_size by task_size - 1.
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* Currently runtime can form batches that exceed maximal batch_size by task_size - 1.
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- We will fix that in the nearest patch.
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+ We will fix that in the nearest patch.
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UARTman