Instructions to use Contrastive-Tension/BERT-Base-NLI-CT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Contrastive-Tension/BERT-Base-NLI-CT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Contrastive-Tension/BERT-Base-NLI-CT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Contrastive-Tension/BERT-Base-NLI-CT") model = AutoModelForMaskedLM.from_pretrained("Contrastive-Tension/BERT-Base-NLI-CT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc694eadf393ccf56bf002d2352d866b8893c9bf66c8043b83ab1f594909866a
- Size of remote file:
- 438 MB
- SHA256:
- 6a87eb55a836ce9d198250937d028bcb989d35c3f3745c58e4263c03b94d6f6b
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