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Let's learn how to use Google AI Studio (gemini 3)
Transcript
[00:00] in today's video we're going to learn how to start fine-tuning Google AI models within Google AI Studio we have the ability to create prompts templates and a ton of other stuff in this video though we're going to learn how to tune a model therefore in today's video I'm going to show you how to tune a model with a structured prompt and a import file sound good let's go and jump into today's video Welcome Back y'all in this video I'm going to show you how to start fine-tuning Google AI models now your first question might be Corbin what do you mean tune a model or fine tune what this does in this context is that we train a model so when we access the AP
[00:30] endpoint or alternatively use it in a user interface like this we expect very specific types of outputs so in this video we're going to go over two different examples here and it's going to make a lot more sense the first example here is going to be a business that wants to create a social media caption generator but be tailored to their brand now I've done a video like this in the past but with open Ai and Chad gbt and you can check it out right there to see how to finetune the Chad gbt model but in this video we're going to fine-tune Gemini no not the Star Sign Gemini are you a Leo are you a Virgo are you a Scorpio let's go ahead and get
[01:01] going here now what's great about Google AI studio is it's free to start so I'm going to leave a link to it in the description below go and check it out but let's go and create a tune model here let's start off by creating a structured prompt we're going to go ahead and simply click create a structured prompt I'm also going to leave a link to their FAQ and guide so if you have any other questions that I may not address in this video you can check it out as well create structured prompt we are in let's go edit our title here we're going to goad and see caption generator boom now comparative to fine-tuning a kgpt model which actually required us to make a Json file within
[01:32] vs code we can actually do the fine-tuning within the UI of Google AI studio so it's a little bit easier all it requests us to do is simply add a potential user input and the expected output now we have a couple different options of how to add this kind of information the second option you're going to see in this video is just simply doing it through a Google sheet or CSV this option though where it's going to manually add our inputs and outputs here's an example of a possible input and a possible output notice the input is K company and the output is Sweet Moments cake emoji # cake love #
[02:03] Sweet Treats therefore the purpose of this fine tune model for this use case is I'm going to provide a company type so for example cake company and then the actual output should consist of a caption one emoji and two hashtags and how we're going to train it to understand to only do one emoji and only do two hashtags is we're going to provide 20 different examples here now Google has identify the best way to go about this is to provide 500 examples but for that context you're better off uploading a while then you know manually inputting each one now before I add the
[02:34] rest of these data points cuz I don't think you want to be there for that we're going to go ahead and look at our settings here now we looking at our settings we have a couple things to take note of here first off choosing our type of model if you're familiar with open AI think of Chad gbt 3.5 Chad gbg4 they have their own versions of models as well now if you want a more in-depth video on the models the pricing and everything above the board there check out my Google AI studio video that's like 9 Minutes of everything you need to know about this platform for now though we're just going to St with 1.5 flash token count as the amount of tokens that are currently being expended through the input and the output now temperature is important but it seems within our
[03:05] structured prompts as of now we can't actually adjust it I want you to think of temperature as a creativity metric basically the higher temperature we have the more creative the AI gets the more crazy it gets you get some pretty crazy answers here that AR really structur it or maybe not a line of what you want the lower temperature it is the more consistent it is at scale on outputs what's good here though is since we're doing a structure prompt anyways we don't have to worry too much about this because we're basically telling you how to interact with inputs now we have some other options here but for now it's not too important for what we're trying to do today let's add the rest of our data
[03:35] points or examples in this context I want ahead and added 10 different examples here of ways I want the input to be and the output to look at a few fitness trainer no paying no gain fitness goals work out dog groming service positively perfect # dog groming # petare notice how each one has an emoji and two hashtags that's the whole use case and purpose of this specific finetune we want to make sure and ensures that these show up on every single caption we do when we put the input of a company type once we put in enough examples and we're satisfied
[04:05] let's see if it works I'm going to Simply put in real estate agency and let's check out the output here we should see one emoji and two hashtags generate response there we go we got home swe home an emoji and two hashtags this shows you the power of fine-tuning a model I'm going to go ahead and hit run down here as well and we can run it as many times as possible so it worked again another one another one another one no I'm not dj calid but there we go it shows consistency and it shows it's working every single time therefore we don't have to worry too much about temperature in this context now in order
[04:36] for us to actually save that structured prompt we need at least 20 examples so let me go and add those I have gone ahead and saved 20 different examples here let's go and save it now what I've noticed in the short term is that the actual button to save doesn't really seem to work so a work around for this is hit these ellipses and save as copy now that I've saved it as a copy I can actually reference it in my new tune model here come in right here copy of capent generator here we go showing me the first example that we saw earlier proceed to choose your tuned model name I'm just going to say my business caption I know very creative short term
[05:06] we can only find tune one type of model for advanced settings we're just going to go a and leave this default once that's all set up all we need to do is hit tune we are loading in what you'll notice is that the way that it will save it in your library is as a tune model comparative to a structured prompt or a chat prompt once it's done it's going to simply be ready to go and updated just now click it you'll get a summary of how it tuned the model and from here to start using it hit use a structured prompt and we can start using our train model Now using the structured prompt is to use it within Google AI Studio to do
[05:38] a little bit more testing see if it works well if you want to use it in the context of an API endpoint within your software or automation you're going to use the model ID here this right here is going to allow us to access this model at an API endpoint on top of that notice how the actual name for the model ID has the name we added earlier so keep that in mind there you go now you successfully know how to find two models Within Google AI Studio make sure you leave a like it's completely free and let's go ahead and see our last step here which is uploading a CSV to create one for this example I went ahead and just created a CSV here with the idea
[06:09] being the input is a state and the output will be a little caption three hashtags and Emoji associated with it now you also have the ability to use a currently existing Google sheet or any file within your drive I'm going to simply just drag and drop my CSV once I've added my CSV here it's going to ask for a little bit of formatting pretty simple because we actually formatted it in the CSV all we to do is this this is the input column so I'm going to say new input column and then this is the output column new output column once we do that we can input our 30 current examples now
[06:39] optimally this is how you're going to upload 500 as you would not want to manually put in 500 entries import examples currently loading once we've imported the data we just follow the same steps I showed earlier and you got your fine tune model but based off imported data now that covers everything we can do when it comes to fine tuning models and Google AI studio now there is other features on this platform that I cover in that other video I referenced earlier so go ahead and check that out also do a ton of other stuff on this channel other than just this so make sure to check that out and I'll see you in the next video I went ahead and let
[07:10] YouTube do its thing and choose the videos to see next I have no clue what they are probably pretty good that's my face and I'll see you in the next video