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WEBVTT
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So we're now going to run a large language model directly on your box using a platform called llama,
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which lets you run C plus plus code version of Llms compiled directly on your machine.
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I'm going to start by showing you on windows, and then we'll flip over to Mac.
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So to start with llama you bring up your favorite browser.
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Let's go to Microsoft Edge.
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And you can simply go to llama.
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Com or just search llama llama it's O followed by llama.
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And the first hit here in the search results will be Alarm.com.
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And here it is.
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It's called llama because it was initially built around a model that's called llama, which is the open
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source model from meta, which really stole the show a couple of years ago when it first came out.
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So downloading is as simple as pressing the download button.
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And once you press the download button, you press download for windows and it will start to download
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the windows version.
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And if I look here at my downloads, I will see that it has downloaded.
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There's a Setup.exe.
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If I press the open file button, it will prompt me.
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Oh, it's still.
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It's still downloading again.
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I just ran this.
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It will prompt me to install it locally, which I will do as soon as it's installed locally.
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You then go to the start menu and you're probably familiar with this, but you bring up a PowerShell
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by typing power in here, and as soon as you do, it prompts you and you press open and up comes a PowerShell,
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which is where we are going right now to run a large language model.
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Minutes into this course and the way we do it is we simply type once.
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Once that install is completed and you pressed okay, you can just simply say olama o l l a m a run.
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And now you put the name of the model next, and the name of the model we're going to use is going to
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be llama 3.2, which is one of the very newest models.
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And so here it goes.
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And it's run.
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It's happening right now.
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That blinking cursor means that we have a large language model running on this computer.
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It might take a bit longer for you the first time.
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It has to download the 2 billion parameters associated with Lama, and depending on your internet connection,
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that might take a little bit, but you'll get a progress bar that will show you what's going on.
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So what we're now going to do is try and talk to this LLM, and we're going to try and do something
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useful with a free LLM.
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And here's what we'll do.
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I'm actually trying to learn Spanish at the moment.
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And I can tell you that my grasp of the Spanish language is distinctly less inferior to my grasp of
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llms.
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And the app that I'm using to try and teach me has a service where you can pay to chat with a with an
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AI tutor.
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Now, I don't want to pay for that because I know I can run an open source model and do it for free.
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So right now we're going to build ourselves a Spanish tutor which will teach me Spanish.
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All open source without paying a penny.
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So I'm going to say I am trying to learn Spanish.
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I am a complete beginner.
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Please chat with me in basic Spanish to teach me.
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And so that is the prompt that we will start with.
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And let's see what happens.
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It's thinking.
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Hola.
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Welcome to our conversation in Spanish.
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To start, let's begin with some basic greetings.
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Como estas?
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So you can see that it's giving me a very good starting prompt.
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It's giving me some examples.
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It understands where I'm coming from.
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And I can now say something like.
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Put an accent on.
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Uh, so.
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Oh, there's a small mistake.
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Okay, there we go.
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It's correcting me.
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I think it's the accent that I missed and maybe the question mark as well, so you get the idea.
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We've actually just built something which has commercial value because indeed, this is sold at a price
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immediately for free on our boxes using an open source LLM that is llms in action from the get go.
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And now for Mac people, let's flip over to a mac.