jev-style How to use chaoliangUNSW/Jev-Style-2B-Decision-v3 with jev-style:
pip install "jev-style[torch]"
from jev_style import JevStyle, noul, choice
js = JevStyle.from_pretrained("chaoliangUNSW/Jev-Style-2B-Decision-v3")
out = js.decide("I was charged twice for one order.", {
"billing": noul("This message is about billing."),
"team": choice("Which team should handle it?", ["billing", "shipping", "tech"]),
})
print(out["answers"]["team"]["choice"]) Transformers How to use chaoliangUNSW/Jev-Style-2B-Decision-v3 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="chaoliangUNSW/Jev-Style-2B-Decision-v3") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("chaoliangUNSW/Jev-Style-2B-Decision-v3")
model = AutoModelForCausalLM.from_pretrained("chaoliangUNSW/Jev-Style-2B-Decision-v3", device_map="auto") 
