Instructions to use artefactory/BERTJudge-Formatted-CR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use artefactory/BERTJudge-Formatted-CR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="artefactory/BERTJudge-Formatted-CR", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("artefactory/BERTJudge-Formatted-CR", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("artefactory/BERTJudge-Formatted-CR", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
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BERT-as-a-Judge is a family of encoder-based models designed for efficient, reference-based evaluation of LLM outputs. Moving beyond rigid lexical extraction and matching, these models evaluate semantic correctness, accommodating variations in phrasing and formatting while using only a fraction of the computational resources required by LLM-as-a-Judge approaches.
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# BERTJudge-Formatted-CR
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BERT-as-a-Judge is a family of encoder-based models designed for efficient, reference-based evaluation of LLM outputs. Moving beyond rigid lexical extraction and matching, these models evaluate semantic correctness, accommodating variations in phrasing and formatting while using only a fraction of the computational resources required by LLM-as-a-Judge approaches.
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