Instructions to use tals/albert-base-vitaminc_flagging with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tals/albert-base-vitaminc_flagging with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tals/albert-base-vitaminc_flagging")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tals/albert-base-vitaminc_flagging") model = AutoModelForSequenceClassification.from_pretrained("tals/albert-base-vitaminc_flagging") - Notebooks
- Google Colab
- Kaggle
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datasets:
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- fever
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- glue
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# Details
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Model used in [Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://aclanthology.org/2021.naacl-main.52/) (Schuster et al., NAACL 21`).
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datasets:
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- fever
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- glue
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- tals/vitaminc
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# Details
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Model used in [Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://aclanthology.org/2021.naacl-main.52/) (Schuster et al., NAACL 21`).
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