Instructions to use SGK86/laya-multilingual-typed-decisions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SGK86/laya-multilingual-typed-decisions with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SGK86/laya-multilingual-typed-decisions", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Laya-multilingual fine-tuned on LocalLLaMA/typed-decisions (RLCD)
Fine-tuned from convaiinnovations/laya-multilingual with the official RLCD recipe (single GPU, effective batch 64, lr encoder 2.5e-5 / head 1e-4, 4 epochs, sigma 0.4->0.1), with post-training temperature calibration.
Official 400-case test set metrics: Accuracy 0.786, Soft Acc 0.507, Brier 0.064, ECE 0.113, Score MAE 0.253.
Reference: TypeSafe Jev 1.13.0 (third-party, BENCHMARKS.md): Acc 0.727, Soft Acc 0.580, Brier 0.148, ECE 0.144, MAE 0.391. Majority baseline: 0.461.
import laya
agent = laya.load("SGK86/laya-multilingual-typed-decisions")
result = agent.predict(state, questions)
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