Text Classification
Transformers
Safetensors
English
qwen3_5_text
text-generation
decider
systemone
jev
decision-model
qwen3.5
post-train
text-to-typed-output
structured-output
classification
tool-calling
routing
moderation
custom-code
Eval Results (legacy)
Instructions to use Jeetu456/decider-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeetu456/decider-2b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeetu456/decider-2b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Jeetu456/decider-2b") model = AutoModelForCausalLM.from_pretrained("Jeetu456/decider-2b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 421 Bytes
cd02163 | 1 2 3 4 5 6 7 8 9 | """Decider 2B: typed decisions for Jev/SystemOne requests, one forward pass per request."""
from ._core import (DeciderModel, SchemaError, encode_record, load_release_model, # noqa: F401
systemone, validate_request)
from .api import Decider
__all__ = ["Decider", "DeciderModel", "SchemaError", "encode_record", "load_release_model", "systemone",
"validate_request"]
__version__ = "2.0.0"
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