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<v Maximilian>So where do you find those open models?</v>

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And with that, I of course mean the ones I just described,

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but maybe also others

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because it's of course not just these four providers

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that do publish open Large Language Models.

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Well, of course if you do want

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to learn more about Meta's Llama models

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or Google's Gemma models,

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their official websites are a great place to go.

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But to get a general overview of available models

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and to explore available models

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and also find new models,

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which you maybe haven't heard about before,

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Hugging Face is the defacto standard place to go.

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Huggingface.co is a website

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that's all about open AI models in the end.

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They have a models catalog

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where all the big players like Meta, Google,

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but also everybody else that's creating AI models,

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publishes those models or lists those models.

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So in that model catalog, you'll find a plethora

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of open Large Language and also other AI models.

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You will, for example,

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find information about Google's Gemma models in there,

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about the Qwen model,

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which is another popular open model,

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about Deepseek models,

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Microsoft's open models,

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and of course also Meta's Llama models, for example.

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And again, many, many more.

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Now in this model catalog, you can sort by trending

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or by most downloads, to also play around

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with the models most other people's maybe using.

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You can also sort based on recency

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to find out which new models have been published

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or what the most liked models are.

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It's also worth noting

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that Hugging Face is not just

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about Large Language Models, though.

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You can filter for which kind

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of AI model you are interested in.

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You, for example, can also explore computer vision models

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that are able to analyze images

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or models that are able to generate images

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or models that can handle audio.

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So there's a broad variety

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of models listed here in this course,

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however, will focus on the Large Language Models,

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which are arguably

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the most popular open models being used out there.

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And what's really great about Hugging Face is

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that you don't just get this model catalog

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where you have this list of models,

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but of course you can also inspect those different models

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and learn more about them.

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For example, if I inspect the Google Gemma 3,

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27 billion parameters model here,

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which is just one possible model

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you could run locally as well,

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you get such a model card

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and every model hosted on Hugging Face has such a card.

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And this card simply describes the model.

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It describes the capabilities of this model, for example,

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that the Gemma model is multimodal.

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It can handle text and image input.

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It describes the context window and anything else

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the provider of that model, Google, in this case,

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felt worth sharing.

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So it's a good way to understand what a model can do.

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You'll also find some code examples

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on how you could use this model in your code,

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though I'll get back to using these models locally,

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including programmatically a little bit later

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in this course.

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And you'll also learn more about the size of this model,

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so the number of parameters it has.

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So that would be 27 billion parameters here

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for this Gemma 3 27 billion model.

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The data type of these parameters

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and some other things to which I'll get back later,

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which are important to understand when it comes

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to running these models locally on your system.

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But again, I will get back to that later.

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The key takeaway here is

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that this Hugging Face models catalog is the place

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to go to explore all available open models

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you could consider running locally or on your own servers.

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It's there for all as a great place to explore

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not just the big well-known model providers

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and their models, but also more niche

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or upcoming open models that might be worth exploring.

