Instructions to use Contrastive-Tension/BERT-Large-NLI-CT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Contrastive-Tension/BERT-Large-NLI-CT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Contrastive-Tension/BERT-Large-NLI-CT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Contrastive-Tension/BERT-Large-NLI-CT") model = AutoModelForMaskedLM.from_pretrained("Contrastive-Tension/BERT-Large-NLI-CT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b5b3f90ced22a5bcd799044e40edcbff300dfd483e94d4ff7a26e8c7f714269
- Size of remote file:
- 1.34 GB
- SHA256:
- 145a3cc54ae880d734c603854a5246b8bf76997a213e1653bed0d1495623f479
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