Comments (4)
@purefire adding an export script is a high priority to unlock model variations / fine tuning. Please chime in #11 on the source format that would be most useful.
Hi @julien-c 👋 :)
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interested as well!
from gemma.cpp.
It's the same model but this repo cannot use those weight formats directly. We have an internal export script that transforms other formats into our simple blob format, but this is not yet ready for production/open-sourcing.
Please comment on #11, which discusses which input formats would be useful.
We do not use Rocm, this repo is currently CPU-only, see #18.
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Consolidating weight export discussions to the issue #11 . We're working on making a script available soon - feel free to chime in with further comments there. Thanks!
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Related Issues (20)
- Using mingw64 build on windows 10 fails HOT 3
- Weights converted from PyTorch don't seem to work properly HOT 2
- Seeking feedbacks for python wrapper of gemma.cpp HOT 3
- Is the format of output Markdown? HOT 2
- Failed on raspberry pi OS (64bit) HOT 6
- TODO (**Optimize, potentially using new VQSort PartialSort**) HOT 1
- again:Cached compressed weights does not exist yet gemma HOT 5
- Implement arch changes
- Have there been any performance comparisons between gemma.cpp and llama.cpp? HOT 3
- Mismatch between expected 1024000 and actual 1024512 KiB size. HOT 1
- Any more fine example or user-guide for CodeGemma?
- How can I get the compiled static executable binary file in linux platform? HOT 2
- Near-term roadmap HOT 3
- Use a MatMul implementation over MatVec for Prefill Computations HOT 2
- Paligemma Support HOT 1
- project does not work as submodule HOT 2
- Error during build process HOT 1
- Compile error on visual studio build, array size exceed HOT 2
- gemma.exe does not respond no matter how long you wait. HOT 3
- Crash in Attention() with huge input HOT 13
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