Instructions to use ModelTC/roberta-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/roberta-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/roberta-base-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/roberta-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/roberta-base-mnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c660035308fc3890f2d5db69f98c6867e3fc2341b4d0c210b3fdaceda24386f0
- Size of remote file:
- 997 MB
- SHA256:
- 2333bf1907199d4cd33693f39ac301b6a9c16d4e09a5eb2f898d568936e7920a
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