uncensored
Neko-Institute-of-Science's picture
Update usage instructions.
f92bcb1
|
raw
history blame
1.03 kB
metadata
datasets:
  - gozfarb/ShareGPT_Vicuna_unfiltered

Convert tools

https://github.com/practicaldreamer/vicuna_to_alpaca

Training tool

https://github.com/oobabooga/text-generation-webui

ATM I'm using 2023.05.04v0 of the dataset and training full context.

Notes:

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 if you have not: https://huggingface.co/Neko-Institute-of-Science/LLaMA-30B-HF
  2. Download the checkpoint-xxxx folder you want and put it in the loras folder.
  3. Load ooba: python server.py --listen --model LLaMA-30B-HF --load-in-8bit --chat --lora checkpoint-xxxx
  4. Select instruct and chose Vicuna-v1.1 template.

Want to see it Training?

https://wandb.ai/neko-science/VicUnLocked/runs/vx8yzwi7