Text Classification
Transformers
Safetensors
English
tiny_jev
feature-extraction
jev
system-one
open-jev
decision-model
calibrated
routing
classification
guardrails
non-autoregressive
custom_code
Instructions to use lostargon/Tiny-Jev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lostargon/Tiny-Jev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lostargon/Tiny-Jev", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lostargon/Tiny-Jev", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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link to Tiny-Jev-1.7B
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Tiny-Jev 0.6B: single-file decision model (backbone + head), model card
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