How to use chaoliangUNSW/Jev-Style-2B-Decision-v4 with jev-style:
pip install "jev-style[torch]"
from jev_style import JevStyle, noul, choice js = JevStyle.from_pretrained("chaoliangUNSW/Jev-Style-2B-Decision-v4") 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"])
How to use chaoliangUNSW/Jev-Style-2B-Decision-v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chaoliangUNSW/Jev-Style-2B-Decision-v4")
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("chaoliangUNSW/Jev-Style-2B-Decision-v4") model = AutoModelForMultimodalLM.from_pretrained("chaoliangUNSW/Jev-Style-2B-Decision-v4", device_map="auto")
