Instructions to use textattack/bert-base-uncased-WNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-WNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-WNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-WNLI") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-WNLI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2526763c36818ce5eb3434c4a0c2d9a0d9e29b1effb1156f2175912fb608918
- Size of remote file:
- 1.05 kB
- SHA256:
- 0d442d564a0855b44749bb63b397eb35cc22a77814c5b943425a0957acc0dea2
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