Maximilian: Now I mentioned that in Power User mode,
you got some extra options here below your responses.
And not just there,
we also got an extra option here,
for example, when we send a message.
This User button here is not there in regular User Mode.
So what are these options all about?
For example, we got this Branch option here,
and this essentially allows you to fork the chat
to create multiple simultaneous parallel chat histories
after a given message.
So, for example, if I click this button here,
you'll see that two chats are created here.
So it's very similar to Duplicate in the end,
where I also duplicate a chat.
It's simply a way for you to have multiple,
parallel chat histories
that are based on the same start of a chat,
but then change from a certain point on,
so where you branch out into different versions of the chat
because you might have different follow up questions.
So if I got a response by the model
and now I have two different follow up questions,
which I don't want to have in the same chat history,
I could branch my chat after this message.
We also have continuous Assistant message,
which is useful if you got a response that seems cut off.
Now that's not the case here,
but if you've got a super long response,
at some point, it may actually be too much
for the model to handle.
They have certain limits
regarding the amount of response tokens
they can generate in one go.
And if that happens, if the response is cut off,
you can always click this button
to have the model continue with the generation
and continue generating a response.
Now, regarding the options down here,
user allows you to actually toggle
between the mode of the message you're about to send.
Now the default is always User
because you are the user of this application,
you are the user interacting with the AI model.
But for advanced use cases,
you also might want to simulate a certain AI response.
You might want to artificially create a chat history
that never happened.
And you can do that by switching between roles.
So if I create a new chat here,
I could start with an Assistant message
which says, "Hi, I am an assistant
and I can help you with using open LLMs locally."
And we could now simulate
that the AI sent back this response
even though it never did.
So if I now sent this,
I still get a response by the large language model.
So it still treats this as if a regular user sent it,
but internally, this will be stored as an Assistant message,
as you also see here.
And that may be interesting for more advanced use cases,
where you then, for example, later down in the chat,
you might want to ask the model what it can do for you.
And it will refer back to its earlier responses,
including responses that it actually never gave you,
but that were faked by you by assigning such a fake role.
Now, this is definitely a niche feature.
I just wanted to mention it since this button is here.
You won't have it in regular User mode.
In Power User mode,
you'll also find an extra sidebar here to the left.
There, you can access your chats,
which is the only option you have in User mode,
which is why you don't even have a sidebar there,
an extra sidebar I mean.
But in Power User mode,
you also got the Developer view here.
So you don't just have that in Developer mode,
but also in Power User mode.
And in there, you'll find more information
about the model that's being loaded.
You can tweak some advanced settings here,
and I'll get back to those later.
And you'll find information
about the web endpoints you could target
if you were building a separate application
that wants to communicate with this loaded model.
You also find potential errors down here.
For example, here for me, it logged an error,
which I got during one response
that was generated by the model.
And you also find some debug logs,
so not just error logs,
that simply print out some information
about the latest generation that was performed by the model.
Now again, I'll get back to these more advanced settings
a little bit later.
You also have a My Models folder here,
which shows you the different models
that have been loaded.
Here, you also find the path to the folder on your system
where these models are stored.
And you can change that path,
open it in Finder or Windows Explorer,
and always reset it back to the default path
if you did change it.
And of course, you also find a list of all the models
that have been downloaded into this directory.
And here you see that we got large language models
or embedding models.
Now embedding models are not the focus of this course.
In the end, embedding models can be used
to create so-called vector embeddings,
which are numerical representations of words and sentences
that also model relationships between words
to describe it in a simple, brief way.
And you can use such models
that create such vector embeddings here in LM Studio
because that could, for example, be irrelevant
if you were building your own RAG application
locally on your system,
your own retrieval augmented generation application,
for example,
which is an advanced way of using generative AI,
which I will cover in my main generative AI course,
but not in this course,
which is about running models locally.
So here you see your large language models,
and you can also manage these download models here.
So you can tweak their default parameters
that will be used as a default
whenever you load such a model into LM Studio.
And again, I'll get back to those later.
And you can also view this specific model
in your Finder or Windows Explorer,
copy the path, view it on Hugging Face,
or also delete it to free up the space on your system.
So that's that.
Last but not least, you got this Discover page,
which gives you this model search page
where you can discover and download new models.