| ▲ | nopelynopington 2 days ago | |||||||||||||||||||||||||
I built it at home this morning and tried it, perhaps my expectations were high but I wasn't terribly impressed. I asked it for a list of ten types of data I might show on a home info display panel. It gave me three. I clarified that I wanted ten, it gave me six. Every request after that just returned the same six things. I know it's not chatGPT4 but I've tried other very small models that run on CPU only and had better results | ||||||||||||||||||||||||||
| ▲ | Me1000 2 days ago | parent | next [-] | |||||||||||||||||||||||||
This is a technology demo, not a model you'd want to use. Because Bitnet models are only average 1.58 bits per weight you'd expect to need the model to be much larger than your fp8/fp16 counterparts in terms of parameter count. Plus this is only a 2 billion parameter model in the first place, even fp16 2B parameter models generally perform pretty poorly. | ||||||||||||||||||||||||||
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| ▲ | ashirviskas 2 days ago | parent | prev [-] | |||||||||||||||||||||||||
> I've tried other very small models that run on CPU only and had better results Maybe you can you share some comparative examples? | ||||||||||||||||||||||||||
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