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