bittensor
koila
bittensor | koila | |
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4 | 7 | |
776 | 1,817 | |
3.9% | - | |
9.6 | 6.8 | |
6 days ago | 21 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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bittensor
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Has anyone else used the bittensor/subnet1 model? Is there a way to use it outside of the horde?
You are connected through the validator "Tensor.Exchange", and I recently upped the amount of workers to enhance its speed. What it runs on the background is literally a mixture of different models working in parallel to give the best response, more information about this can be found on www.bittensor.com or on their Discord.
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LLM@home
Today I came across bittensor / Tao network. https://github.com/opentensor/bittensor
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[D] I don't really trust papers out of "Top Labs" anymore
Have a look at Bittensor - www.bittensor.com
- Bittensor: Internet-Scale Neural Networks
koila
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How to fix CUDA out of memory with Koila?
but I always get CUDA out of memory . Long story short I found koila which should fix this issue, but I'm not sure how to add this to my code. in their page they have (input, label) = lazy(input, label, batch=0) but i kinda feel lost. can you help me please.
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Pytorch CUDA out of memory persists after lowering batch size and clearing gpu cache
Having 53760 neurons takes much memory. Try adding more Conv2D layers or play with stride. Also, try .detach() to data and labels after training. Lastly, I would suggest to take a look at https://github.com/rentruewang/koila. Have not tried yet but it should be helpful.
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[D] Would the 8gb VRAM of the 3060ti mean that some models in computer vision cannot be trained with it at all?
Tools like this can help: https://github.com/rentruewang/koila
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[P] Dynamic batching for GPT-J API
You could take a look at how these guys are determining memory batch size limits... https://github.com/rentruewang/koila
- Koila: Prevent PyTorch's out of memory error with lazy evaluation
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Solve PyTorch's `CUDA error: out of memory` in 1 line of code
Project Link
- Show HN: Solve `CUDA error: out of memory` in one line of code
What are some alternatives?
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gpt-j-api-huggingface
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