WEBVTT 00:00.500 --> 00:07.280 So we're now going to run a large language model directly on your box using a platform called llama, 00:07.280 --> 00:14.330 which lets you run C plus plus code version of Llms compiled directly on your machine. 00:14.360 --> 00:17.810 I'm going to start by showing you on windows, and then we'll flip over to Mac. 00:17.840 --> 00:21.560 So to start with llama you bring up your favorite browser. 00:21.590 --> 00:22.880 Let's go to Microsoft Edge. 00:22.880 --> 00:24.950 And you can simply go to llama. 00:24.980 --> 00:31.310 Com or just search llama llama it's O followed by llama. 00:31.820 --> 00:35.660 And the first hit here in the search results will be Alarm.com. 00:35.660 --> 00:36.650 And here it is. 00:36.680 --> 00:42.230 It's called llama because it was initially built around a model that's called llama, which is the open 00:42.230 --> 00:47.480 source model from meta, which really stole the show a couple of years ago when it first came out. 00:47.480 --> 00:51.230 So downloading is as simple as pressing the download button. 00:51.230 --> 00:56.210 And once you press the download button, you press download for windows and it will start to download 00:56.210 --> 00:57.740 the windows version. 00:57.950 --> 01:02.930 And if I look here at my downloads, I will see that it has downloaded. 01:02.930 --> 01:04.380 There's a Setup.exe. 01:04.560 --> 01:07.530 If I press the open file button, it will prompt me. 01:07.530 --> 01:08.100 Oh, it's still. 01:08.130 --> 01:09.000 It's still downloading again. 01:09.030 --> 01:09.630 I just ran this. 01:09.660 --> 01:15.240 It will prompt me to install it locally, which I will do as soon as it's installed locally. 01:15.600 --> 01:21.060 You then go to the start menu and you're probably familiar with this, but you bring up a PowerShell 01:21.090 --> 01:27.630 by typing power in here, and as soon as you do, it prompts you and you press open and up comes a PowerShell, 01:27.630 --> 01:31.920 which is where we are going right now to run a large language model. 01:31.920 --> 01:36.780 Minutes into this course and the way we do it is we simply type once. 01:36.810 --> 01:44.280 Once that install is completed and you pressed okay, you can just simply say olama o l l a m a run. 01:44.280 --> 01:49.290 And now you put the name of the model next, and the name of the model we're going to use is going to 01:49.290 --> 01:55.020 be llama 3.2, which is one of the very newest models. 01:55.860 --> 01:57.060 And so here it goes. 01:57.060 --> 01:58.020 And it's run. 01:58.020 --> 01:59.400 It's happening right now. 01:59.400 --> 02:03.060 That blinking cursor means that we have a large language model running on this computer. 02:03.060 --> 02:04.770 It might take a bit longer for you the first time. 02:04.770 --> 02:10.210 It has to download the 2 billion parameters associated with Lama, and depending on your internet connection, 02:10.210 --> 02:13.870 that might take a little bit, but you'll get a progress bar that will show you what's going on. 02:14.230 --> 02:18.460 So what we're now going to do is try and talk to this LLM, and we're going to try and do something 02:18.460 --> 02:20.020 useful with a free LLM. 02:20.020 --> 02:21.250 And here's what we'll do. 02:21.280 --> 02:23.620 I'm actually trying to learn Spanish at the moment. 02:23.620 --> 02:28.630 And I can tell you that my grasp of the Spanish language is distinctly less inferior to my grasp of 02:28.630 --> 02:29.350 llms. 02:29.710 --> 02:36.730 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 02:36.730 --> 02:37.720 AI tutor. 02:37.750 --> 02:42.370 Now, I don't want to pay for that because I know I can run an open source model and do it for free. 02:42.370 --> 02:48.130 So right now we're going to build ourselves a Spanish tutor which will teach me Spanish. 02:48.490 --> 02:51.400 All open source without paying a penny. 02:51.400 --> 02:57.460 So I'm going to say I am trying to learn Spanish. 02:58.660 --> 03:01.960 I am a complete beginner. 03:04.690 --> 03:12.000 Please chat with me in basic Spanish to teach me. 03:13.200 --> 03:15.630 And so that is the prompt that we will start with. 03:15.630 --> 03:16.830 And let's see what happens. 03:16.830 --> 03:17.820 It's thinking. 03:18.390 --> 03:19.230 Hola. 03:19.590 --> 03:21.480 Welcome to our conversation in Spanish. 03:21.510 --> 03:24.570 To start, let's begin with some basic greetings. 03:24.630 --> 03:25.800 Como estas? 03:26.250 --> 03:30.540 So you can see that it's giving me a very good starting prompt. 03:30.540 --> 03:31.890 It's giving me some examples. 03:31.890 --> 03:33.930 It understands where I'm coming from. 03:33.960 --> 03:36.240 And I can now say something like. 03:40.980 --> 03:42.120 Put an accent on. 03:42.450 --> 03:44.550 Uh, so. 03:44.670 --> 03:46.410 Oh, there's a small mistake. 03:51.000 --> 03:52.050 Okay, there we go. 03:52.050 --> 03:52.710 It's correcting me. 03:52.710 --> 03:58.320 I think it's the accent that I missed and maybe the question mark as well, so you get the idea. 03:58.320 --> 04:03.870 We've actually just built something which has commercial value because indeed, this is sold at a price 04:03.870 --> 04:11.790 immediately for free on our boxes using an open source LLM that is llms in action from the get go. 04:11.790 --> 04:14.700 And now for Mac people, let's flip over to a mac.