fix

README.md

@@ -15,6 +15,7 @@ Making evaluating and fine-tuning LLaMA models with low-rank adaptation (LoRA) e
 * Fine-tune LLaMA models with different prompt templates and training dataset format.<br /><a href="https://youtu.be/5Db9U8PsaUk"><img width="640px" src="https://user-images.githubusercontent.com/3784687/230277315-9a91d983-1690-4594-9d54-912eda8963ee.gif" /></a>
   * Load JSON and JSONL datasets from your folder, or even paste plain text directly into the UI.
   * Supports Stanford Alpaca [seed_tasks](https://github.com/tatsu-lab/stanford_alpaca/blob/main/seed_tasks.jsonl), [alpaca_data](https://github.com/tatsu-lab/stanford_alpaca/blob/main/alpaca_data.json) and [OpenAI "prompt"-"completion"](https://platform.openai.com/docs/guides/fine-tuning/data-formatting) format.
+  * Use prompt templates to keep your dataset DRY.
 
 
 ## How to Start

llama_lora/utils/data.py

@@ -11,7 +11,6 @@ def init_data_dir():
     parent_directory_path = os.path.dirname(current_file_path)
     project_dir_path = os.path.abspath(
         os.path.join(parent_directory_path, "..", ".."))
-    os.makedirs(os.path.join(Global.data_dir, "lora_models"), exist_ok=True)
     copy_sample_data_if_not_exists(os.path.join(project_dir_path, "templates"),
                                    os.path.join(Global.data_dir, "templates"))
     copy_sample_data_if_not_exists(os.path.join(project_dir_path, "datasets"),