From the course: Generative AI: Working with Large Language Models
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GitHub models
From the course: Generative AI: Working with Large Language Models
GitHub models
- [Narrator] Imagine asking two teachers to explain the same mathematics problem to a class. Now each of them might have a different approach to solving the problem. And it's like that with large language models. You can provide the same text or prompt and get a different response from the large language model. GitHub models let us easily compare two large language models. You'll need a GitHub account, and you can sign up for one by going to github.com. And once you have an account, head over to github.com/marketplace. And here you can just select Models over on the left, and then you can select models based on the different providers, their capability, and then their functionality, so things like whether you need a model that has low latency, whether you want a model that can handle multiple languages, and so on. Now the OpenAI models, in general, are pretty good. So I'm going to use the GPT‑4o mini as my benchmark, and I want to compare this to one of the smaller models. And so…
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Contents
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GPT-34m 32s
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GPT-3 use cases5m 27s
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Challenges and shortcomings of GPT-34m 17s
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GLaM3m 6s
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Megatron-Turing NLG Model1m 59s
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Gopher5m 23s
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Scaling laws3m 14s
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Chinchilla7m 53s
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BIG-bench4m 24s
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PaLM5m 49s
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OPT and BLOOM2m 51s
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GitHub models2m 43s
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Accessing Large Language Models using an API6m 25s
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Inference time vs. pre-training4m 5s
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