Tianqi Chen

Thanks for th suggestion, deploying to mobile would involve more checks, so likely we are going to follow a release schedule in future and not doing nightly for apks

we are movig towards a JIT based SDK system in https://llm.mlc.ai/docs/deploy/android.html which hopefully allows latest features to be incorporated by directly re-runing the `mlc_llm package`. We likely wont do nightly...

@sebastienbo sorry just wan to clarify, we would like to host APK for stable releases :) e.g. with major models, i just mention that in near term it would be...

As of now our focus has been on GPU and possibly NPU. CPU can in theory be supported as TVM have cpu backends, so we also welcome contributions to try...

Thanks for reporting @nobuhiroYamakado you can skip the model meta data as they are displayed during compile. @CharlieFRuan i guess this is also the case for webllm. @MasterJH5574 let us...

Thank you @nobuhiroYamakado, these are very valuable suggestions. Do you mind send a PR to https://github.com/mlc-ai/mlc-llm/blob/main/docs/deploy/ios.rst removing the model metadata step and add what you suggested?

Thanks @srkreddy1238 ! We are considering transition away ChatModule and remove it in future, see https://github.com/mlc-ai/mlc-llm/issues/2217 for some background. Perhaps we can bring a simpler version like debug chat which...

closing for now as we ar emoving towards the MLCEngine, we can explore possibility of CLI kit for android in mlc engine, one idea is perhaps we can use kotlin...

The latest build should solve the issue for GPU, we still do not yet have cpu support

cc @MasterJH5574 @anibohara2000 @Celve @Hzfengsy