Instructions to use pingzhili/switch-base-32-finetuned-hotpotqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pingzhili/switch-base-32-finetuned-hotpotqa with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pingzhili/switch-base-32-finetuned-hotpotqa") model = AutoModelForSeq2SeqLM.from_pretrained("pingzhili/switch-base-32-finetuned-hotpotqa") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
The switch-base-32 model was fine-tuned on the HotpotQA dataset.
Validation exact-match/F1-score: 67.55/84.60.
The prompt key in PromptSource: "generate_answer_affirmative".
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