Instructions to use SantiagoCorley/multibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SantiagoCorley/multibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SantiagoCorley/multibert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SantiagoCorley/multibert") model = AutoModelForSequenceClassification.from_pretrained("SantiagoCorley/multibert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Verified signatureThis model is a BERT model trained for multi labeled classification using the UCC dataset [1]. This model is currently part of the pipeline of Detoxigram. This model uses the bert-uncased tokenizer. Price, I., Gifford-Moore, J., Fleming, J., Musker, S., Roichman, M., Sylvain, G., ... & Sorensen, J. (2020). Six attributes of unhealthy conversation. arXiv preprint arXiv:2010.07410.2d3478a
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