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Thanks for releasing this! What is your use case for this rather than llama.cpp? For the on-device AI stuff I mostly do, llama.cpp is better because of GPU/meta
by rgbrgb 3y ago
Thanks for releasing this! What is your use case for this rather than llama.cpp? For the on-device AI stuff I mostly do, llama.cpp is better because of GPU/metal offloading.
- austinvhuang 3y agollama.cpp is great, if it fit your needs you can use it. I think at this point llama.cpp is effectively a platform that's hardened for production. In its current form, I think of gemma.cpp is more of a direct model implementation (somewhere between the minimalism of llama2.c and the generality of ggml). I tend to think of 3 modes of usage: - hacking on inference internals - there's very little indirection, no IRs, the model is just code, so if you want to add support for your own runtime support for sparsity/quantization/model compression/etc. and demo it working with gemma, there's minimal barriers to do so - implementing experimental frontends - i'll add some examples of this in the very near future. but you're free to get pretty creative with terminal UIs, code that interact with model internals like the KV cache, accepting/rejecting tokens etc. - interacting with the model locally with a small program - of course there's other options for this but hopefully this is one way to play with gemma w/ minimal fuss.
- castles 3y ago> accepting/rejecting tokens etc. That sounds interesting