Instructions to use sagnikrayc/bert-base-cased-fever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagnikrayc/bert-base-cased-fever with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sagnikrayc/bert-base-cased-fever")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sagnikrayc/bert-base-cased-fever") model = AutoModelForSequenceClassification.from_pretrained("sagnikrayc/bert-base-cased-fever") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a821f7b1e7433d4b5408c95bd8ab7bbcc70bf8ed157e2e24f16385772d4aee56
- Size of remote file:
- 433 MB
- SHA256:
- 804b1f7f206008aac8a37d250ef84012147d056bf410c7ca1017448bca0b7a51
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