Instructions to use RuyuanWan/SBIC_RoBERTa_Text_Disagreement_Binary_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RuyuanWan/SBIC_RoBERTa_Text_Disagreement_Binary_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RuyuanWan/SBIC_RoBERTa_Text_Disagreement_Binary_Classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RuyuanWan/SBIC_RoBERTa_Text_Disagreement_Binary_Classifier") model = AutoModelForSequenceClassification.from_pretrained("RuyuanWan/SBIC_RoBERTa_Text_Disagreement_Binary_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from RuyuanWan/SBIC_RoBERTa_Text_Disagreement_Binary_Classifier: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
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https://huggingface.co/RuyuanWan/SBIC_RoBERTa_Text_Disagreement_Binary_Classifier/resolve/main/tokenizer.json
- Command line
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hf download hf://RuyuanWan/SBIC_RoBERTa_Text_Disagreement_Binary_Classifier/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/RuyuanWan/SBIC_RoBERTa_Text_Disagreement_Binary_Classifier/resolve/main/tokenizer.json
2.11 MB
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