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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90a661d7a25f229d77070712df60f23a4af27e2c0297bde58dc82cf962b463e4
- Size of remote file:
- 499 MB
- SHA256:
- 6db61b4cfea1facac1be224aca47ae7fa39dfcbbe12d500668889316b3ae990d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.