Instructions to use artefactory/BERTJudge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use artefactory/BERTJudge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="artefactory/BERTJudge", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("artefactory/BERTJudge", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("artefactory/BERTJudge", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Intended Use
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These models are designed as sequence classifiers that output a sigmoid score indicating answer correctness. For inference, we
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### Installation
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## Intended Use
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These models are designed as sequence classifiers that output a sigmoid score indicating answer correctness. For inference, we suggest using the [BERT-as-a-Judge](https://github.com/artefactory/BERT-as-a-Judge) package. In most scenarios, we specifically recommend **BERTJudge-Free-QCR** for its superior and more robust evaluation performance.
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### Installation
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