Instructions to use alinet/bart-base-balanced-ra-qg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alinet/bart-base-balanced-ra-qg with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alinet/bart-base-balanced-ra-qg") model = AutoModelForSeq2SeqLM.from_pretrained("alinet/bart-base-balanced-ra-qg") - Notebooks
- Google Colab
- Kaggle
Update metadata with huggingface_hub
Browse files
README.md
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- type: bertscore
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value: 0.6270323888350072
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name: BERTScore Precision
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---
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A question generation model trained on `alinet/balanced_qg` dataset (`resolved_augmented` subset).
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- type: bertscore
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value: 0.6270323888350072
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name: BERTScore Precision
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value: 0.6320889797976309
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name: BERTScore Recall
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---
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A question generation model trained on `alinet/balanced_qg` dataset (`resolved_augmented` subset).
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