Text Classification
jev-style
Safetensors
minicpm
minicpm5
system-one
decision-model
probability
calibration
agent
routing
Instructions to use link921/CPM-jev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- jev-style
How to use link921/CPM-jev with jev-style:
pip install "jev-style[torch]"
from jev_style import JevStyle, noul, choice js = JevStyle.from_pretrained("link921/CPM-jev") 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"]) - Notebooks
- Google Colab
- Kaggle
File size: 369 Bytes
257d034 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | import json
import os
from inference import DecisionModel
model = DecisionModel(".", base_model=os.getenv("CPM_JEV_BASE_MODEL", "openbmb/MiniCPM5-2B-Base"))
result = model.decide(
state="The previous tool call failed twice.",
question="What should the agent do next?",
options=["retry", "switch_tool", "ask_user"],
)
print(json.dumps(result, indent=2))
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