Instructions to use prajjwal1/roberta-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prajjwal1/roberta-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prajjwal1/roberta-base-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prajjwal1/roberta-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("prajjwal1/roberta-base-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 813389faff12d82b45b39ba52c73d07e1915c54d50769fdfc9ad60322d4cac38
- Size of remote file:
- 501 MB
- SHA256:
- a740026c33bb656e47da8adf7db087c11c90b88d47950e5683d308788928784c
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