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:
- 655d3f6803c619aa34c31a027ce74a315eaa200aad3fca5b968dcdf6485bfba2
- Size of remote file:
- 12.8 MB
- SHA256:
- 5f9e4d4901a92b997e463c1f46055088b6cca5ca61a6522d1b9f64c4bb81cb42
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