Text Classification
Transformers
Safetensors
English
Korean
qwen3_5
image-text-to-text
ztc
answer-verification
hallucination-detection
zero-token
confidence-estimation
Instructions to use FINAL-Bench/ZTC-Judge-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FINAL-Bench/ZTC-Judge-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FINAL-Bench/ZTC-Judge-9B")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("FINAL-Bench/ZTC-Judge-9B") model = AutoModelForMultimodalLM.from_pretrained("FINAL-Bench/ZTC-Judge-9B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 089e2bb46c82cdff70c30c03cd8e35fa5eba0e874320d9b2e4260efbd0ea94fd
- Size of remote file:
- 16.8 MB
- SHA256:
- 80557c58cfce3f4802f3ef069d2f8d6893c8096a57f5a2afa241b2060c870d6d
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