Update README.md

README.md

@@ -41,7 +41,7 @@ Below are the results of Vicuna-style testing: 80 questions in various categorie
 | Writing        | 8             | 19                   | 19                 |
 | Total          | 125           | 271                  | 312                |
 
-A csv of questions, answers and GPT's reviews are also included in this repo in the /TestResults/ folder, along with the base model for comparison.
+A csv of questions, answers and GPT's reviews are also included in the [Eluwa github repo](https://github.com/yudhanjaya/Eluwa) in the /TestResults/ folder, along with the base model for comparison.
 
 Because of its small size, Eluwa can be used as research into conversational models with older and slower hardware. 
 ## Using Eluwa
@@ -53,8 +53,7 @@ To load Eluwa, download [OPT 2.7b from Huggingface](https://huggingface.co/faceb
 ## Training and notes
 
 Training Eluwa is a straightforward process. It is essentially Facebook's GPT-like OPT 2.7b model, loaded in 8-bit and trained using [Stanford's Alapaca dataset](https://github.com/tatsu-lab/stanford_alpaca). 
-Use the [Colab notebook here](https://huggingface.co/BackyardLabs/Eluwa/blob/main/Train_eluwa.ipynb). I've written notes in there on what the functions do. 
- 
+The training code is available on the [Eluwa github repo](https://github.com/yudhanjaya/Eluwa).
 
 ## Why "Eluwa"?