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
model card: language tag en only
Browse files
README.md
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base_model: Qwen/Qwen3-0.6B
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language:
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- en
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- ru
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pipeline_tag: text-classification
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library_name: transformers
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tags:
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base_model: Qwen/Qwen3-0.6B
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language:
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- en
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pipeline_tag: text-classification
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library_name: transformers
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tags:
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