More context for your Pascal GPU or older!
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More context for your Pascal GPU or older!
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Update: Now available in the official releases of KoboldCpp!
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Update: Now available in the official releases of KoboldCpp!
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[releases] 
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[releases] 
https://github.com/LostRuins/koboldcpp/releases/latest
https://github.com/LostRuins/koboldcpp/releases/latest
link
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These are great news for all the users with GTX 10XX, P40...
text
These are great news for all the users with GTX 10XX, P40...
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Flash Attention implementation for older NVIDIA GPUs without requiring Tensor Cores has come to llama.cpp in the last few days, and should be merged in the next version of KoboldCpp, you can already try it with another fork or by building it.
text
Flash Attention implementation for older NVIDIA GPUs without requiring Tensor Cores has come to llama.cpp in the last few days, and should be merged in the next version of KoboldCpp, you can already try it with another fork or by building it.
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[Mentioned KCPP fork] 
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[Mentioned KCPP fork] 
https://github.com/Nexesenex/kobold.cpp/releases/latest
https://github.com/Nexesenex/kobold.cpp/releases/latest
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[PR] 
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[PR] 
https://github.com/ggerganov/llama.cpp/pull/7188
https://github.com/ggerganov/llama.cpp/pull/7188
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You should expect less VRAM usage for the same context, allowing you to experience higher contexts with your current GPU.
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You should expect less VRAM usage for the same context, allowing you to experience higher contexts with your current GPU.
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There have also been reported final tokens/second speed improvements for inference, so that's also grand!
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There have also been reported final tokens/second speed improvements for inference, so that's also grand!
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If you have tried it, I'd like to hear your experiences with --flashattention so far, especially for this implementation and for the large number of Pascal (GTX 10XX, P40...) cards.
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If you have tried it, I'd like to hear your experiences with --flashattention so far, especially for this implementation and for the large number of Pascal (GTX 10XX, P40...) cards.
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Discussion linked bellow, with more links to relevant information:
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Discussion linked bellow, with more links to relevant information:
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https://huggingface.co/LWDCLS/LLM-Discussions/discussions/11
https://huggingface.co/LWDCLS/LLM-Discussions/discussions/11
link
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Cheers!
text
Cheers!
More context for your Pascal GPU or older!

Update: Now available in the official releases of KoboldCpp!
[releases] https://github.com/LostRuins/koboldcpp/releases/latest

These are great news for all the users with GTX 10XX, P40...

Flash Attention implementation for older NVIDIA GPUs without requiring Tensor Cores has come to llama.cpp in the last few days, and should be merged in the next version of KoboldCpp, you can already try it with another fork or by building it.

[Mentioned KCPP fork] https://github.com/Nexesenex/kobold.cpp/releases/latest

[PR] https://github.com/ggerganov/llama.cpp/pull/7188

You should expect less VRAM usage for the same context, allowing you to experience higher contexts with your current GPU.

There have also been reported final tokens/second speed improvements for inference, so that's also grand!

If you have tried it, I'd like to hear your experiences with --flashattention so far, especially for this implementation and for the large number of Pascal (GTX 10XX, P40...) cards.

Discussion linked bellow, with more links to relevant information:

https://huggingface.co/LWDCLS/LLM-Discussions/discussions/11

Cheers!
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