Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v3-small
deberta-v3
deberta
nli
natural-language-inference
multitask
multi-task
pipeline
extreme-multi-task
extreme-mtl
tasksource
zero-shot
rlhf
Instructions to use tasksource/deberta-small-long-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tasksource/deberta-small-long-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="tasksource/deberta-small-long-nli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tasksource/deberta-small-long-nli") model = AutoModelForSequenceClassification.from_pretrained("tasksource/deberta-small-long-nli") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba60fa4c8ea2b1beaebaff81950a4adf2da50c1a00061aee583ca4a9968bb716
- Size of remote file:
- 568 MB
- SHA256:
- 9af30c7ad7235a2054300bc2df1d98149ad6008dd1ef06212be8b32b5d1b3458
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