From d6d691ec6892417785ec2fb4b520d83d413790ae Mon Sep 17 00:00:00 2001 From: lucylq Date: Wed, 24 Jul 2024 13:51:39 -0700 Subject: [PATCH] Add llama3.1 to readme (#4378) Summary: https://github.com/pytorch/executorch/pull/4376 Pull Request resolved: https://github.com/pytorch/executorch/pull/4378 Reviewed By: kirklandsign Differential Revision: D60177343 Pulled By: lucylq fbshipit-source-id: f8197e7af18785bfcca3c5c2980ec1bd7acdaf9d --- examples/models/llama2/README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/examples/models/llama2/README.md b/examples/models/llama2/README.md index e59adf37c5..0ab35b2c50 100644 --- a/examples/models/llama2/README.md +++ b/examples/models/llama2/README.md @@ -5,7 +5,7 @@ For more details, see [Llama 2 repo](https://github.com/facebookresearch/llama) Pretrained models are not included in this repo. Users are suggested to download them [here](https://ai.meta.com/resources/models-and-libraries/llama-downloads/). -# What are Llama 2 and 3? +# What is Llama? Llama is a collection of large language models that use publicly available data for training. These models are based on the transformer architecture, which allows it to process input sequences of arbitrary length and generate output sequences of variable length. One of the key features of Llama models is its ability to generate coherent and contextually relevant text. This is achieved through the use of attention mechanisms, which allow the model to focus on different parts of the input sequence as it generates output. Additionally, Llama models use a technique called “masked language modeling” to pre-train the model on a large corpus of text, which helps it learn to predict missing words in a sentence. Llama models have shown to perform well on a variety of natural language processing tasks, including language translation, question answering, and text summarization and are also capable of generating human-like text, making Llama models a useful tool for creative writing and other applications where natural language generation is important. @@ -59,6 +59,9 @@ Note that since Llama3's vocabulary size is 4x that of Llama2, we had to quantiz |Galaxy S24 | 10.91 tokens/second | 11.21 tokens/second | |OnePlus 12 | 10.85 tokens/second | 11.02 tokens/second | +### Llama3.1 +> :warning: **use the main branch**: Llama3.1 is supported on the ExecuTorch main branch (not release 0.3). + # Instructions ## Tested on