3 ms·
It has 480B parameters total, apparently. You would only need 512GB of RAM if you were running at 8-bit. It could probably fit into 256GB at 4-bit, and 4-bit qu
by coder543 2y ago
It has 480B parameters total, apparently. You would only need 512GB of RAM if you were running at 8-bit. It could probably fit into 256GB at 4-bit, and 4-bit quantization is broadly accepted as a good trade-off these days. Still... that's a lot of memory.
EDIT: This[0] confirms 240GB at 4-bit.
[0]: https://github.com/ggerganov/llama.cpp/issues/6877#issue-2261479840 https://github.com/ggerganov/llama.cpp/issues/6877#issue-226...
- refulgentis 2y agoYeah, and usually GPU RAM, unless you enjoy waiting for a minute for filling the context :(
- kaibee 2y agoI know quantizing larger models seems to be more forgiving but I’m wondering if that applies less to these extreme-MoE models. It seems to be that it should be more like quantizing a 3B model.
- coder543 2y ago4-bit is fine for models of all sizes, in my experience. The only reason I personally don’t quantize tiny models very much is because I don’t have to, not because the accuracy gains from running at 8-bit or fp16 are that great. I tried out 4-bit Phi-3 yesterday, and it was just fine.