WEBVTT

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What more is there to say, really?

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Tomorrow is the day for results.

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A day that very excited indeed about.

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Uh.

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But I will mention everything that you can do at this point generating text and code with frontier models

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and their APIs, open source models through hugging faces, various libraries, tools, assistance,

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rag.

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It's all part of your skill set.

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You can follow the five step strategy I went through to solve problems including curating data, building

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a baseline model, and fine tuning frontier model with example training sets in those jsonl the JSON

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lines files that we uploaded, and now and now you can run Q Laura fine tuning for open source models,

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including defining and selecting your hyperparameters.

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And then you can run training and you can monitor training.

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And a great joy it is to uh, so tomorrow, you will be able to run inference on a fine tuned model,

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which isn't as simple as it sounds, because you can't just load it in.

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You have to know how to load in the base model and apply these chullora weights on top of it.

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But it's not that difficult.

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But but it is.

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There are a couple of steps to it.

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Uh, and then, of course, we'll take a moment to look at the results.

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Um, but most importantly, at that point, you will be able to carry out the end to end process from

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first idea and thought and definition of the commercial problem through to having a trained model,

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uh, to build your own proprietary verticalized LLM to solve a business problem.

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And I was going to try and put a third bullet in there, because I've normally had three bullets against

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the what you'll be able to do tomorrow.

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But it seems to me like that second bullet is enough of a mic drop that it's like you don't need a third

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bullet.

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That's all you need.

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That second bullet, it says it all.

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That's what you're going to be able to do.

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And it's huge.

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I'll see you then.