Instructions to use erickfm/t5-small-finetuned-bias with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erickfm/t5-small-finetuned-bias with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("erickfm/t5-small-finetuned-bias") model = AutoModelForSeq2SeqLM.from_pretrained("erickfm/t5-small-finetuned-bias") - Notebooks
- Google Colab
- Kaggle
This model is a fine-tune checkpoint of T5-small, fine-tuned on the Wiki Neutrality Corpus (WNC), a labeled dataset composed of 180,000 biased and neutralized sentence pairs that are generated from Wikipedia edits tagged for “neutral point of view”. This model reaches an accuracy of 0.32 on a dev split of the WNC.
For more details about T5, check out this model card.
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