Transformers
Safetensors
English
scientific-claim-verification
scifact
evidence-selection
retrieved-evidence
Instructions to use rishhh/verisci-claim-verifier-learned-selector-joint-seed123 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rishhh/verisci-claim-verifier-learned-selector-joint-seed123 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rishhh/verisci-claim-verifier-learned-selector-joint-seed123", device_map="auto") - Notebooks
- Google Colab
- Kaggle
VeriSci Learned Selector Joint Verifier
Experimental candidate with a learned claim-sentence selector and joint verifier.
- Selector base:
microsoft/deberta-v3-small - Verifier base:
rishhh/verisci-claim-verifier-retrieval-adapted-seed123 - SciFact validation accuracy: 0.7022
- SciFact validation macro F1: 0.6653
- Promotion gate passed:
False - Promotion gate reason:
candidate_accuracy_below_target: 0.702 < 0.910
This artifact is experimental unless the repository documentation marks it as promoted.
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