Improve exporting Llama docs

Author: jakmro

docs/docs/guides/exporting-llama.mdx

@@ -1,23 +1,39 @@
 ---
-title: Exporting LLaMa
+title: Exporting Llama
 sidebar_position: 2
 ---
 
 In order to make the process of export as simple as possible for you, we created a script that runs a Docker container and exports the model. 
 
-1. Get a [HuggingFace](https://huggingface.co/) account. This will allow you to download needed files. You can also use the [official LLaMa website](https://www.llama.com/llama-downloads/). 
-2. Pick the model that suits your needs. Before you download it, you'll need to accept a license. For best performance, we recommend using Spin-Quant or QLoRA versions of the model:
-   - [LLaMa 3.2 3B](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct/tree/main/original)
-   - [LLaMa 3.2 1B](https://huggingface.co/meta-llama/Llama-3.2-1B/tree/main/original)
-   - [LLaMa 3.2 3B Spin-Quant](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct-SpinQuant_INT4_EO8/tree/main)
-   - [LLaMa 3.2 1B Spin-Quant](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8/tree/main)
-   - [LLaMa 3.2 3B QLoRA](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct-QLORA_INT4_EO8/tree/main)
-   - [LLaMa 3.2 1B QLoRA](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct-QLORA_INT4_EO8/tree/main)
-3. Download the `consolidated.00.pth`, `params.json` and `tokenizer.model` files. If you can't see them, make sure to check the `original` directory. Sometimes the files might have other names, for example `original_params.json`.
-4. Run `mv tokenizer.model tokenizer.bin`. The library expects the tokenizers to have .bin extension.
-5. Run `./build_llama_binary.sh --model-path /path/to/consolidated.00.pth --params-path /path/to/params.json script that's located in the `llama-export` directory. 
-6. The script will pull a Docker image from docker hub, and then run it to export the model. By default the output (llama3_2.pte file) will be saved in the `llama-export/outputs` directory. However, you can override that behavior with the `--output-path [path]` flag.
+## Steps to export Llama
+### 1. Create an Account:
+Get a [HuggingFace](https://huggingface.co/) account. This will allow you to download needed files. You can also use the [official Llama website](https://www.llama.com/llama-downloads/). 
 
+### 2. Select a Model:
+Pick the model that suits your needs. Before you download it, you'll need to accept a license. For best performance, we recommend using Spin-Quant or QLoRA versions of the model:
+   - [Llama 3.2 3B](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct/tree/main/original)
+   - [Llama 3.2 1B](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct/tree/main/original)
+   - [Llama 3.2 3B Spin-Quant](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct-SpinQuant_INT4_EO8/tree/main)
+   - [Llama 3.2 1B Spin-Quant](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8/tree/main)
+   - [Llama 3.2 3B QLoRA](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct-QLORA_INT4_EO8/tree/main)
+   - [Llama 3.2 1B QLoRA](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct-QLORA_INT4_EO8/tree/main)
+
+### 3. Download Files:
+Download the `consolidated.00.pth`, `params.json` and `tokenizer.model` files. If you can't see them, make sure to check the `original` directory.
+
+### 4. Rename the Tokenizer File:
+Rename the `tokenizer.model` file to `tokenizer.bin` as required by the library:
+```bash
+mv tokenizer.model tokenizer.bin
+```
+
+### 5. Run the Export Script:
+Navigate to the `llama_export` directory and run the following command: 
+```bash
+./build_llama_binary.sh --model-path /path/to/consolidated.00.pth --params-path /path/to/params.json
+```
+
+The script will pull a Docker image from docker hub, and then run it to export the model. By default the output (llama3_2.pte file) will be saved in the `llama-export/outputs` directory. However, you can override that behavior with the `--output-path [path]` flag.
 
 :::note[Note]
 This Docker image was tested on MacOS with ARM chip. This might not work in other environments.