Instructions to use textattack/roberta-base-MNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/roberta-base-MNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/roberta-base-MNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/roberta-base-MNLI") model = AutoModelForSequenceClassification.from_pretrained("textattack/roberta-base-MNLI", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00ca197d03e957e0a3bfae0de7e8418ecfebdede84b1eec1a5a29625028ca1a5
- Size of remote file:
- 501 MB
- SHA256:
- 78cdd92748c783dc90adb723db76c5197fb4f75ce85b06351bf8e90b0682ee11
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