Instructions to use korca/textfooler-roberta-base-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use korca/textfooler-roberta-base-rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="korca/textfooler-roberta-base-rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("korca/textfooler-roberta-base-rte") model = AutoModelForSequenceClassification.from_pretrained("korca/textfooler-roberta-base-rte") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f589426534dbc57578c91bb23c3277fde98bdbe87940d71b91e1ca685dd3b49d
- Size of remote file:
- 499 MB
- SHA256:
- ae60ace3b30fde7b8d4514d4b8834302a2868b4109a2b8bfb0fbd047c0b7e511
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