Thanks for the link! I actually use SD a lot practically so it’s been taking up like 95% of my attention in the AI space. I have LM Studio on my Mac and it blazes through responses with the 7b model and tends to meet most of my non-coding needs.
Can you explain what you mean here?
Personally I prefer avoiding fine tuned models wherever possible and just working more on crafting longer constrained contexts for pretrained models with a pre- or post-processing layer to format requests and results in acceptable ways if needed (latency permitting, but things like Groq are fast enough this isn’t much of an issue).
Are you saying better initial prompting on a raw pre-trained model?
Yeah. So with the pretrained models they aren’t instruct tuned so instead of “write an ad for a Coca Cola Twitter post emphasizing the brand focus of ‘enjoy life’” you need to do things that will work for autocompletion like:
As an example of our top shelf social media copywriting services, consider the following Cleo winning tweet for the client Coca-Cola which emphasized their brand focus of “enjoy life”:
In terms of the pre- and post-processing, you can use cheaper and faster models to just convert a query or response from formatting for the pretrained model into one that is more chat/instruct formatted. You can also check for and filter out jailbreaking or inappropriate content at those layers too.
Basically the pretrained models are just much better at being more ‘human’ and unless what you are getting them to do is to complete word problems or the exact things models are optimized around currently (which I think poorly map to real world use cases), for a like to like model I prefer the pretrained.
Though ultimately the biggest advantage is the overall model sophistication - a pretrained simpler and older model isn’t better than a chat/instruct tuned more modern larger model.
Thanks for the link! I actually use SD a lot practically so it’s been taking up like 95% of my attention in the AI space. I have LM Studio on my Mac and it blazes through responses with the 7b model and tends to meet most of my non-coding needs.
Can you explain what you mean here?
Are you saying better initial prompting on a raw pre-trained model?
Yeah. So with the pretrained models they aren’t instruct tuned so instead of “write an ad for a Coca Cola Twitter post emphasizing the brand focus of ‘enjoy life’” you need to do things that will work for autocompletion like:
In terms of the pre- and post-processing, you can use cheaper and faster models to just convert a query or response from formatting for the pretrained model into one that is more chat/instruct formatted. You can also check for and filter out jailbreaking or inappropriate content at those layers too.
Basically the pretrained models are just much better at being more ‘human’ and unless what you are getting them to do is to complete word problems or the exact things models are optimized around currently (which I think poorly map to real world use cases), for a like to like model I prefer the pretrained.
Though ultimately the biggest advantage is the overall model sophistication - a pretrained simpler and older model isn’t better than a chat/instruct tuned more modern larger model.