Instructions to use dipta007/coverage-judge-balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dipta007/coverage-judge-balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dipta007/coverage-judge-balanced")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dipta007/coverage-judge-balanced") model = AutoModelForSequenceClassification.from_pretrained("dipta007/coverage-judge-balanced") - Notebooks
- Google Colab
- Kaggle
Improve model card with metadata and paper references
#1
by nielsr HF Staff - opened
This PR improves the model card for the DecomposeRL "Tiny Judge" model. It adds:
- Relevant metadata (
pipeline_tag,library_name,license). - Links to the research paper, the official GitHub repository, and the project page.
- A description of the model as a distilled ModernBERT classifier for claim verification.
This ensures the model is correctly categorized on the Hugging Face Hub and provides necessary context for users.