Introduction of Llama 3
Llama 3 is an AI large model usage platform. Users can use the latest Llama 3 large model launched by Meta AI.
Llama 3 is free to use, users just need to visit the link below.
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How to Use Llama 3
We use the Llama 3 large model. Different types of large models are provided on the left side of the page, including the Llama 3 8 billion parameter version and the Llama 3 70 billion parameter version, as well as three different versions of the Llama 2 large model.
Llama 3 is launched by technology company Meta and is considered the best open source large model on the market. It adopts the Transformer architecture and uses more than 15T public data for training. Its training data volume is 7 times that of the Llama 2 large model, its code amount is 4 times that of the Llama 2 large model, and its effect is also better than that of Llama 2.
We use the Llama 3 big model and let it explain the Transformers architecture to a five years old child. The explanation given by Llama 3 is as follows:
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!
Summary
As an AI large model usage platform, users can experience Llama 3 large models for free.
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