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Update examples/README.md with Llama 3 and names #3275

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7 changes: 4 additions & 3 deletions examples/README.md
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Expand Up @@ -9,6 +9,7 @@ ExecuTorch's extensive support spans from simple modules like "Add" to comprehen
## Directory structure
```
examples
├── llm_manual # A storage place for the files that [LLM Maunal](https://pytorch.org/executorch/main/llm/getting-started.html) needs
├── models # Contains a set of popular and representative PyTorch models
├── portable # Contains end-to-end demos for ExecuTorch in portable mode
├── selective_build # Contains demos of selective build for optimizing the binary size of the ExecuTorch runtime
Expand All @@ -20,7 +21,7 @@ examples
| └── mps # Contains end-to-end demos of MPS backend
├── arm # Contains demos of the Arm TOSA and Ethos-U NPU flows
├── qualcomm # Contains demos of Qualcomm QNN backend
├── xtensa # Contains demos of exporting and running a simple model on Xtensa Hifi4 DSP
├── cadence # Contains demos of exporting and running a simple model on Xtensa DSPs
├── third-party # Third-party libraries required for working on the demos
└── README.md # This file
```
Expand All @@ -30,9 +31,9 @@ examples

A user's journey may commence by exploring the demos located in the [`portable/`](./portable) directory. Here, you will gain insights into the fundamental end-to-end workflow to generate a binary file from a ML model in [portable mode](../docs/source/concepts.md##portable-mode-lean-mode) and run it on the ExecuTorch runtime.

## Demo of Llama2
## Demo of Llama 2 and Llama 3

[This page](./models/llama2/README.md) demonstrates how to run a Llama 2 7B model on mobile via ExecuTorch. We use XNNPACK to accelerate the performance and 4-bit groupwise PTQ quantization to fit the model on Android and iOS mobile phones.
[This page](./models/llama2/README.md) demonstrates how to run Llama 2 7B and Llama 3 8B models on mobile via ExecuTorch. We use XNNPACK to accelerate the performance and 4-bit groupwise PTQ quantization to fit the model on Android and iOS mobile phones.

## Demo of Selective Build

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