Update README.md

README.md

@@ -43,8 +43,8 @@ There are two main steps
 
 ## Download the model from Huggingface
 To use the model, you can run it with TorchTune commands. I have provided the necessary Python code to automate the process. Follow these steps to get started:
-- Download the fintuned version `meta_model_0.pt` file (see the `files` tap in this page).
-- Save the model file in the following directory: `/home/USERNAME/Meta-Llama-3-8B/`
+1- Download the fintuned version `meta_model_0.pt` file (see the `files` tap in this page).
+2- Save the model file in the following directory: `/home/USERNAME/Meta-Llama-3-8B/`
 
 ## Using the model
 
@@ -192,11 +192,11 @@ python command.py
 
 We fine-tuned the `Meta-Llama-3-8B` model by two key steps: preparing the dataset and executing the fine-tuning process.
 
-### Prepare the Dataset
+### 1- Prepare the Dataset
 
 For this fine-tuning, we utilized the [QueryBridge dataset](https://huggingface.co/datasets/aorogat/QueryBridge), specifically the pairs of questions and their corresponding tagged questions. However, before we can use this dataset, it is necessary to convert the data into instruct prompts suitable for fine-tuning the model. You can find these prompts at [this link](https://huggingface.co/datasets/aorogat/Questions_to_Tagged_Questions_Prompts). Download the prompts and save them in the directory: `/home/YOUR_USERNAME/data`
 
-### Fine-Tune the Model
+### 2- Fine-Tune the Model
 
 To fine-tune the `Meta-Llama-3-8B` model, we leveraged [Torchtune](https://pytorch.org/torchtune/stable/index.html). Follow these steps to complete the process: