update README.md

README.md

@@ -11,7 +11,7 @@ Making evaluating and fine-tuning LLaMA models with low-rank adaptation (LoRA) e
 
 * **[1-click up and running in Google Colab](#run-on-google-colab)** with a standard GPU runtime.
   * Loads and stores data in Google Drive.
-* Evaluate various LLaMA LoRA models stored in your folder or from Hugging Face.<br /><a href="https://youtu.be/A3kb4VkDWyY"><img width="640px" src="https://user-images.githubusercontent.com/3784687/230272844-09f7a35b-46bf-4101-b15d-4ddf243b8bef.gif" /></a>
+* Evaluate various LLaMA LoRA models stored in your folder or from Hugging Face.<br /><a href="https://youtu.be/IoEMgouZ5xU"><img width="640px" src="https://user-images.githubusercontent.com/3784687/231023326-f28c84e2-df74-4179-b0ac-c25c4e8ca001.gif" /></a>
 * 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.
@@ -28,6 +28,8 @@ There are various ways to run this app:
 
 ### Run On Google Colab
 
+*See [video](https://youtu.be/lByYOMdy9h4) for step-by-step instructions.*
+
 Open [this Colab Notebook](https://colab.research.google.com/github/zetavg/LLaMA-LoRA-Tuner/blob/main/LLaMA_LoRA.ipynb) and select **Runtime > Run All** (`⌘/Ctrl+F9`).
 
 You will be prompted to authorize Google Drive access, as Google Drive will be used to store your data. See the "Config"/"Google Drive" section for settings and more info.