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    1. Really impressive results out of Meta here.

      Super crazy that their GPQA scores are that high considering they tested at 0-shot. I almost worry there might be some leakage.

      Super excited for what the big Llama-3 is going to bring to the table.

    2. Some interesting notes.

      * 8b parameter version and 70b parameter version. 
      * decoder only architecture. 
      * Text in to text out only on the models (currently). 
      * Plans to release multimodal versions of llama 3 later 
      * Plans to release larger context windows later. 
      * It generally sounds like they’re going for an iterative release. 
      * Pretrained on 15 trillion tokens. 
      * Trained on 2 24k GPU clusters. 
      * New more efficient tokenizer and a vocabulary of 128k tokens. 
      * Have versions still in training internally at over 400b parameters. 
      * Created an internal evaluation that was never given to the modeling team in order to avoid overfitting. 

    3. How does it compare with GPT-4 in the “Instruct Human” evaluation? They only compared with GPT 3.5 according to the diagram but maybe I missed it in the article

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