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
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# Model Card for Model ID
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Continuous fine-tuning of deberta-tasksource, fine-tuned on newer tasksource and with context length of size 1024.
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Upcoming: longer training + 1280 tokens context length.
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# Model Card for Model ID
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Continuous fine-tuning of deberta-tasksource, fine-tuned on newer tasksource and with context length of size 1024.
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Upcoming: longer training + 1280 tokens context length.
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