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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2990796914e3b388c84e817ed4fc0c67f8aacad93b07b4cfd153b0338b4673f1
- Size of remote file:
- 3.06 kB
- SHA256:
- 32eb09f8f1c1bc135d8b7a83ebb2056f7c2a507ccbbdb829960ed237c7e0b0d4
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