Update 4-Prepare-LLaMA-models.md

Author: pareenaverma

content/learning-paths/smartphones-and-mobile/Build-Llama3-Chat-Android-App-Using-Executorch-And-XNNPACK/4-Prepare-LLaMA-models.md

@@ -8,26 +8,26 @@ layout: learningpathall
 
 ## Download and export the Llama 3.2 1B model
 
-To get started with Llama 3, you can obtain the pre-trained parameters by visiting [Meta's Llama Downloads](https://llama.meta.com/llama-downloads/) page. Request access by filling out your details, and read through and accept the Responsible Use Guide. This grants you a license and a download link which is valid for 24 hours. The Llama 3.2 1B model is used for this exercise, but the same instructions apply to other options as well with minimal modification.
+To get started with Llama 3, you can obtain the pre-trained parameters by visiting [Meta's Llama Downloads](https://llama.meta.com/llama-downloads/) page. Request access by filling out your details, and read through and accept the Responsible Use Guide. This grants you a license and a download link which is valid for 24 hours. The Llama 3.2 1B Instruct model is used for this exercise, but the same instructions apply to other options as well with minimal modification.
 
 Install the `llama-stack` package from `pip`.
 ```bash
 pip install llama-stack
 ```
 Run the command to download, and paste the download link from the email when prompted.
 ```bash
-llama model download --source meta --model-id Llama3.2-1B
+llama model download --source meta --model-id Llama3.2-1B-Instruct
 ```
 
 When the download is finished, the installation path is printed as output.
 ```output
-Successfully downloaded model to /<path-to-home>/.llama/checkpoints/Llama3.2-1B
+Successfully downloaded model to /<path-to-home>/.llama/checkpoints/Llama3.2-1B-Instruct
 ```
 
 Verify by viewing the downloaded files under this path:
 
 ```bash
-ls $HOME/.llama/checkpoints/Llama3.2-1B
+ls $HOME/.llama/checkpoints/Llama3.2-1B-Instruct
 checklist.chk           consolidated.00.pth     params.json             tokenizer.model
 ```
 
@@ -39,10 +39,10 @@ Export model and generate `.pte` file. Run the Python command to export the mode
 
 ```bash
 python3 -m examples.models.llama.export_llama \
---checkpoint $HOME/.llama/checkpoints/Llama3.2-1B/consolidated.00.pth \
---params $HOME/.llama/checkpoints/Llama3.2-1B/params.json \
+--checkpoint $HOME/.llama/checkpoints/Llama3.2-1B-Instruct/consolidated.00.pth \
+--params $HOME/.llama/checkpoints/Llama3.2-1B-Instruct/params.json \
 -kv --use_sdpa_with_kv_cache -X --xnnpack-extended-ops -qmode 8da4w \
---group_size 256 -d fp32 \
+--group_size 64 -d fp32 \
 --metadata '{"get_bos_id":128000, "get_eos_ids":[128009, 128001, 128006, 128007]}' \
 --embedding-quantize 4,32 \
 --output_name="llama3_1B_kv_sdpa_xnn_qe_4_128_1024_embedding_4bit.pte" \