The title, pretty much.
I’m wondering whether a 70b model quantized to 4bit would perform better than a 7b/13b/34b model at fp16. Would be great to get some insights from the community.
The title, pretty much.
I’m wondering whether a 70b model quantized to 4bit would perform better than a 7b/13b/34b model at fp16. Would be great to get some insights from the community.
In my experience, the lower you go…the model:
- hallucinates more (one time I asked Llama2 what made the sky blue and it freaked out and generated thousands of similar questions line by line)
- is more likely to give you an inaccurate response when it doesn’t hallucinate
- is significantly more unreliable and non-deterministic (seriously, providing the same prompt can cause different answers!)
At the bottom of this post, I compare the 2-bit and 8-bit extreme ends of Code Llama Instruct model with the same prompt and you can see how it played out: https://about.xethub.com/blog/comparing-code-llama-models-locally-macbook
That was useful and interesting.
Speaking of hypothetical situations how much money do you think an individual would need to buy the computing power needed to provide themselves with a gpt 4 turbo like experience locally?