update README.md

README.md

@@ -12,7 +12,7 @@ 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/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>
+* Fine-tune LLaMA models with different prompt templates and training dataset format.<br /><a href="https://youtu.be/IoEMgouZ5xU?t=60"><img width="640px" src="https://user-images.githubusercontent.com/3784687/231026640-b5cf5c79-9fe9-430b-8d4e-7346eb9567ad.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.