Instructions to use tasksource/deberta-base-long-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tasksource/deberta-base-long-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="tasksource/deberta-base-long-nli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tasksource/deberta-base-long-nli") model = AutoModelForSequenceClassification.from_pretrained("tasksource/deberta-base-long-nli") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa237f15372c20fc6aa5f69928bb348440138f2057f51b35f608807c7efab3ad
- Size of remote file:
- 738 MB
- SHA256:
- 71cace06873870322ffa93e4005999961cef6d6b08263b01aad832ded23d94ae
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