Instructions to use LoWiki/Roberta-multilabel-classifier_randompairs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LoWiki/Roberta-multilabel-classifier_randompairs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LoWiki/Roberta-multilabel-classifier_randompairs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LoWiki/Roberta-multilabel-classifier_randompairs") model = AutoModelForSequenceClassification.from_pretrained("LoWiki/Roberta-multilabel-classifier_randompairs") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("LoWiki/Roberta-multilabel-classifier_randompairs")
model = AutoModelForSequenceClassification.from_pretrained("LoWiki/Roberta-multilabel-classifier_randompairs")Quick Links
- Model Card for Model ID
- Model Details
- Uses
- Bias, Risks, and Limitations
- How to Get Started with the Model
- Training Details
- Evaluation
- Model Examination [optional]
- Environmental Impact
- Technical Specifications [optional]
- Citation [optional]
- Glossary [optional]
- More Information [optional]
- Model Card Authors [optional]
- Model Card Contact
- Downloads last month
- 30
Paper for LoWiki/Roberta-multilabel-classifier_randompairs
Paper • 1910.09700 • Published • 54
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LoWiki/Roberta-multilabel-classifier_randompairs")