readme 4

README.md

@@ -19,7 +19,7 @@ _I used to have a video here, but I privated it for now._
 
 ## Training your own model
 
-Model weights are not provided because GitHub doesn't like very large files. But, you can train your own model simply by initializing a ```venv``` and installing ```mlx```, no other libraries needed, then running ```main.py```. When you run it, you will be prompted with the mode, ```0``` being train on dataset and ```1``` being chat. You will have to configure your own dataset by modifying the code (to run dataset mode), but you should be able to run chat mode without modifying anything if you have weights already.
+Model weights (in ```.safetensors```) are not provided because GitHub doesn't like very large files. But, you can train your own model simply by initializing a ```venv``` and installing ```mlx```, no other libraries needed, then running ```main.py```. When you run it, you will be prompted with the mode, ```0``` being train on dataset and ```1``` being chat. You will have to configure your own dataset by modifying the code (to run dataset mode), but you should be able to run chat mode without modifying anything if you have weights already.
 
 Once it begins training, you can safely ^C the program and it will save weights. It should also periodically save weights if I'm not mistaken. The saved weights include the internal memory so the model will remember that the next time it runs. You can launch into chat mode and the memory should carry on from whatever it was learning in training.