Llama 3AI大模型使用平台

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Llama 3介绍

Llama 3是一款AI大模型使用平台，用户可以使用Meta AI最新推出的Llama 3大模型。

Llama 3可以免费使用，用户只需要访问下方链接。

如何使用Llama 3AI

我们使用Llama 3大模型，页面左侧提供了不同类型的大模型，包括Llama 3 80亿参数的版本和Llama 3 700亿参数的版本，以及Llama 2大模型的三个不同版本。Llama 3由科技公司Meta推出，被认为是市场上最好的开源大模型。它采用了Transformer架构，并使用了超过15T公开数据进行训练。它的训练数据量是Llama 2大模型的7倍，代码数量是Llama 2大模型的4倍，其使用效果也优于Llama 2。

我们使用Llama 3大模型，让其解释Transformers架构，Llama 3给出的解释如下：

Imagine you have a toy box with different toys like blocks, dolls, and cars. Each toy has a special feature, like the blocks can build a castle, the dolls can talk, and the cars can move.

When you want to play with the toys, you need to focus on one toy at a time. But, what if you want to build a castle with the blocks and use the dolls to be the castle’s guards? You need to look at both the blocks and the dolls together!

That’s kind of like what the self-attention mechanism does. It helps the Transformer model look at all the “toys” (words or parts of words) in a sentence at the same time and figure out which ones are important to focus on together.

It does this by creating three special friends: Query, Key, and Value.

* Query is like the “what do I want to do?” friend. It looks at each toy and asks, “What’s special about you?”

* Key is like the “what’s your superpower?” friend. It looks at each toy and says, “Oh, you can build castles!”

* Value is like the “let’s use your superpower!” friend. It takes the answers from Key and uses them to help Query.

When Query, Key, and Value work together, they create a special score that says how important each toy is to focus on. Then, they add up these scores to get a final answer!

So, when we use this self-attention mechanism with many layers and many toys (words), it helps the Transformer model understand complex sentences and relationships between words really well!