I'm enthusiastic about BitNet and the potential of low-bit LLMs - the papers show impressive perplexity scores matching full-precision models while drastically reducing compute and memory requirements. What's puzzling is we're not seeing any major providers announce plans to leverage this for their flagship models, despite the clear efficiency gains that could theoretically enable much larger architectures. I suspect…
Microsoft BitNet: inference framework for 1-bit LLMs
21–30 of 36 posts
Re: Microsoft BitNet: inference framework for 1-bit LLMs
#22Sorry for a stupid question but to clarify, even though it is a 1-bit model, it is supposed to be working with any types of embeddings, even taken from larger LLMs(in their example, they use HF1BitLLM/Llama3-8B-1.58-100B-tokens). I.e. it doesn't have an embedding layer built-in and relies on embedding provided separately?
Re: Microsoft BitNet: inference framework for 1-bit LLMs
#23Can anyone help me understand how this works without special bitnet precision-specific hardware? Is special hardware unnecessary? Maybe it just doesn't reach the full bitnet potential without it? Or maybe it does, with some fancy tricks? Thanks!
Re: Microsoft BitNet: inference framework for 1-bit LLMs
#24I'm enthusiastic about BitNet and the potential of low-bit LLMs - the papers show impressive perplexity scores matching full-precision models while drastically reducing compute and memory requirements. What's puzzling is we're not seeing any major providers announce plans to leverage this for their flagship models, despite the clear efficiency gains that could theoretically enable much larger architectures. I suspect…
Re: Microsoft BitNet: inference framework for 1-bit LLMs
#25Can anyone help me understand how this works without special bitnet precision-specific hardware? Is special hardware unnecessary? Maybe it just doesn't reach the full bitnet potential without it? Or maybe it does, with some fancy tricks? Thanks!
The major benefit would be its significant decrease in memory consumption, rather than the compute itself. The major bottleneck of the current LLM infra is typically memory bandwidth and that's the reason why those chip industries are going crazy on HBM. Surely compute optimization helps but this is useful even without any hardware changes.
Re: Microsoft BitNet: inference framework for 1-bit LLMs
#26I'm glad Microsoft uses Bash in the example, instead of their own Windows shells. As a user I would like having something like "Git Bash" for Windows built in the system, as default shell.
Not sure what you mean by “default shell”. The default shell on Windows is this: https://en.wikipedia.org/wiki/Windows_shell. I don’t suppose you mean booting into Bash. Windows doesn’t have any other notion of a default shell.
Re: Microsoft BitNet: inference framework for 1-bit LLMs
#27Re: Microsoft BitNet: inference framework for 1-bit LLMs
#28Re: Microsoft BitNet: inference framework for 1-bit LLMs
#29Earlier quoted context omitted.
Probably because it has relatively painless GPU sharing with pass through. As far as I know that sort of feature requires a hypervisor-level VM, which is not something you get with VirtualBox.
Someone correct me if I'm wrong, but I think you can use a KVM or QEMU backend for VirtualBox and that way get GPU pass-through. Probably not out of the box though.
Re: Microsoft BitNet: inference framework for 1-bit LLMs
#30I'm glad Microsoft uses Bash in the example, instead of their own Windows shells. As a user I would like having something like "Git Bash" for Windows built in the system, as default shell.
Just install Cygwin. Not sure what you mean by “default shell”. The default shell on Windows is this: https://en.wikipedia.org/wiki/Windows_shell . I don’t suppose you mean booting into Bash. Windows doesn’t have any other notion of a default shell.