this thing is super powerful, I'm getting extremely good results
@gustephens1118 ай бұрын
Would you be willing to copy and paste any examples? (Prompt -> output)
@hamdanuk210 ай бұрын
I like your videos! no bull$$, and you jump into the core stuff. Great content. Thank you
@Vermino10 ай бұрын
<a href="#" class="seekto" data-time="209">3:29</a> - oh no, not an uncensored model! That sounds like a feature to me.
@engineerprompt10 ай бұрын
:)
@michaelmitchell22137 ай бұрын
Hi, could you explain what the value is in having GPT4 not issue a disclaimer of neutrality?
@Vermino7 ай бұрын
@@michaelmitchell2213 A value of a disclaimer (if it is neutral) would be to create more context or help provide resources to further a user's inquiry. However, a uncensored model isn't about disclaimers. It's about data is suppressed from the user for supposedly "The Greater Good". Example: You ask Dall-e to generate an image in the artstyle of a famous artist (to save on tokens) with other keywords to make it unique. The response is the LLM actually lying to you that it can't generate it due to [y] and not [x], where [x] is the real reason but [y] is the lie.
@BionicAnimations6 ай бұрын
Please make a video on OpenHermes Neural 7B Q4. It's even better to me. 😍
@Nihilvs10 ай бұрын
very nice ! looking forward to using this one !
@girrajjangid468110 ай бұрын
I tried it out. Results are good.
@giovanith10 ай бұрын
I did the same question (CEO of Twitter), and here is the answer: "The current CEO of Twitter is Jack Dorsey. He has been the CEO of Twitter since 2015, and has also served as the company's CEO from 2006 to 2008. Prior to his time as CEO, Dorsey was the co-founder and CTO of Twitter. He has also been the CEO of Square, a mobile payments company."
@NoidoDev10 ай бұрын
I think it could be a problem, if you test it with the same old questions, since they might have used that for training and optimized for it.
@modolief9 ай бұрын
Thanks!!
@debatradas159710 ай бұрын
thanks
@-someone-.10 ай бұрын
How long before y’all realised it wasn’t bugs and mosquitos on ya screen😅
@s0ckpupp3t10 ай бұрын
totally!
@warsin864110 ай бұрын
Yipee!!!❤
@jondo768010 ай бұрын
I'm curious if other finetuns like vicuna or wizard can bring more out of it or if the "instruct" model is already using all what's possible. I don't understand why they called it instruct because if I understand it right it's a chat model?
@caiyu53810 ай бұрын
Great
@Apps_Guide10 ай бұрын
Can this answer to analytics questions as well from tabular data.
@REplayer0018 ай бұрын
Question: how they measure the model against the others on why it's better?
@engineerprompt8 ай бұрын
Usually people use benchmark datasets. But, I think old benchmarks are not a good way of evaluating this models.
@REplayer0018 ай бұрын
@@engineerprompt I tried this model out, it works fast and gives correct info. However do you know what it is designed for? It seemed like if I try to ask anything other than very technical questions it always gave me "As an Ai model I cannot.. etc etc etc.." One of the things I asked it to give me was a joke, it just couldn't.
@valentinfontanger496210 ай бұрын
Would that fit in a 3080 rtx 10 gb ?
@amortalbeing10 ай бұрын
isthere any difference between the quantized model and the raw model?
@engineerprompt10 ай бұрын
Is the virtual env able to detect the gpu drivers? that might the issue.
@godned7410 ай бұрын
If the word "push" is displayed on an actual mirror, the reflective surface would serve no purpose for people on the opposite side. In such a case, the logical action would be to push the door. the example should use a window and not a mirror.
@therealsharpie10 ай бұрын
Completely agree. The hypothetical itself needs a bit of work.
@user-pk4hn1uz1k5 ай бұрын
Total noob here could someone explain what a "model" is supposed to produce that is actually useful. I see that there is design pattern called RAG that I guess you would use for a "model"?
@christiansroy10 ай бұрын
How many 7B models fact checks? How many 13B models do fact checks? How many 34B parameters model do fact checking ? It’s my understanding that By design, no LLM can do fact checks because they don’t have access to the Internet. I would think that In order for them to fact check, they need access to the Internet, which then becomes an actual application that uses the LLM. The model itself is just weights. Right?
@a2202410 ай бұрын
How would checking to see if (certain) internet sources agree constitute checking a fact?
@RedAnimus10 ай бұрын
It's not like there is a database of facts on the internet. Facts can be reliant on the context of the observer. So, if we asked the AI to tell us if we revolve around the sun, the model would have to assume the time period of the observer and retrieve the relevant fact. If we want it to base the fact on medieval astronomy, then that fact changes based on context. What about competing views? One side or many might see their viewpoint as "fact" and assume the model is flawed because there are studies or evidence that support their specific view. Scientific studies and evidence can be contradicting. Which side is fact? Just saying all this to point out that facts are a difficult thing to pin down. Access to internet solves nothing. It just provides more information. Information that in itself is often biased by those reporting the results in ways that lie about the data. Most use cases likely only need "good enough" reliability, just look at the way we make shortcuts ourselves by using categories, assumptions, estimates, and create stories about how things work even if we know nothing about the systems we interact with on a daily basis. Human minds are terrible at precision. For those use cases, we rely on mathematics, and even then, we have equations in physics and other areas, which are sometimes best guesses, and those still work quite well. Doesn't mean it is fact.