update notes

README.md

@@ -11,16 +11,17 @@ https://github.com/oobabooga/text-generation-webui
 ATM I'm using 2023.05.04v0 of the dataset and training full context.
 
 # Notes:
-So im only training 1 epoch as full context 30b takes a long time to train.
-My 1 epoch will take me 8 days lol but lucly the LoRA feels fully functinal at epoch 1 as shown on my 13b one.
-Also I will be uploading checkpoints almost everyday.
+So I will only be training 1 epoch, as full context 30b takes so long to train.
+This 1 epoch will take me 8 days lol but luckily these LoRA feels fully functinal at epoch 1 as shown on my 13b one.
+Also I will be uploading checkpoints almost everyday. I could train another epoch if there's enough want for it.
 
 # How to test?
 1. Download LLaMA-30B-HF: https://huggingface.co/Neko-Institute-of-Science/LLaMA-30B-HF
 2. Replace special_tokens_map.json and tokenizer_config.json using the ones on this repo.
 3. Rename LLaMA-30B-HF to vicuna-30b
-4. Load ooba: ```python server.py --listen --model vicuna-30b --load-in-8bit --chat --lora checkpoint-xxxx```
-5. Instruct mode: Vicuna-v1 it will load Vicuna-v0 by defualt
+4. Download the checkpoint-xxxx you want and put it in the loras folder.
+5. Load ooba: ```python server.py --listen --model vicuna-30b --load-in-8bit --chat --lora checkpoint-xxxx```
+6. Instruct mode: Vicuna-v1, ooba will load Vicuna-v0 by defualt
 
 
 # Want to see it Training?