Instructions to use Multiperspective/roberta-human-label with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Multiperspective/roberta-human-label with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Multiperspective/roberta-human-label")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Multiperspective/roberta-human-label") model = AutoModelForSequenceClassification.from_pretrained("Multiperspective/roberta-human-label") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9ff0bbd716b879e017a3d682c9e13755ec70972853e7164febb2f72859260c5
- Size of remote file:
- 1.42 GB
- SHA256:
- 0e64bf39fb2f216ecd0897c782015d2507ead10144f950e20e67bb85bf130204
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