fgs218ok/WikiEditBias
Viewer • Updated • 1.56M • 45
How to use fgs218ok/WikiEditBias200k with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="fgs218ok/WikiEditBias200k") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("fgs218ok/WikiEditBias200k")
model = AutoModelForSequenceClassification.from_pretrained("fgs218ok/WikiEditBias200k", device_map="auto")The distilRoberta-base model finetuned on WikiEditBias dataset on the format of edit diff data and 200k samples.
For training data, please ref: https://huggingface.co/datasets/fgs218ok/WikiEditBias/viewer/train200k_val2k_test2k_edit_diff
The input should be in diff format:
<old_text>{old_sentence1} ... {old_sentenceN}<new_text>{new_sentence1} ... {new_sentenceN}
For example:
<old_text>He is a boy.<new_text>He is a nice boy
model = AutoModel.from_pretrained("fgs218ok/WikiEditBias200k")
tokenizer = AutoTokenizer.from_pretrained("fgs218ok/WikiEditBias200k")
This model achieves the 83.45% accuracy on fgs218ok/WikiEditBias200k dataset, outperforms GPT-3.5-turbo by large margin while competitive to GPT4o: