Instructions to use dipta007/answer-judge-balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dipta007/answer-judge-balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dipta007/answer-judge-balanced")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dipta007/answer-judge-balanced") model = AutoModelForSequenceClassification.from_pretrained("dipta007/answer-judge-balanced") - Notebooks
- Google Colab
- Kaggle
Improve model card: add metadata and project links
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community science team. I noticed this model card was mostly empty. This PR adds relevant metadata and links to the paper, code, and project page to make it easier for researchers to understand and use your work. It also provides a brief description of the model's role as a "Tiny Judge" in the DecomposeRL framework.