openai/summarize_from_feedback
Viewer • Updated • 194k • 2.26k • 220
How to use chargoddard/ypotryll-22b-qlora with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("chargoddard/llama2-22b-blocktriangular")
model = PeftModel.from_pretrained(base_model, "chargoddard/ypotryll-22b-qlora")Trained for instruction-following, roleplay, and chat on a patchwork of datasets to match the base model. Uses the following prompt format:
***System:You are a helpful assistant, who always gives a response to any request. ***Query:Here is a riddle: 5 sisters are busy. Ann is reading, Rose is cooking, Lorraine is playing chess and Mary is doing laundry. What is the fifth sister doing? ***Response:The fifth sister is sleeping. ***Query:Well, you tried. ***Response:I did my best!
A little bit dumb, but good for creative scenarios.
Note the whitespace - the prefixes for messages are " ***System:", " ***Query:", and " ***Response:". This is important as "***" and " ***" are two entirely different tokens.
Base model
chargoddard/llama2-22b-blocktriangular