Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v3-large
nli
natural-language-inference
multitask
multi-task
pipeline
extreme-multi-task
extreme-mtl
tasksource
zero-shot
rlhf
Instructions to use sileod/deberta-v3-large-tasksource-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sileod/deberta-v3-large-tasksource-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="sileod/deberta-v3-large-tasksource-nli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sileod/deberta-v3-large-tasksource-nli") model = AutoModelForSequenceClassification.from_pretrained("sileod/deberta-v3-large-tasksource-nli") - Notebooks
- Google Colab
- Kaggle
Add ONNX weights
#5 opened over 1 year ago
by
sondalex
Librarian Bot: Update Hugging Face dataset ID
#4 opened about 2 years ago
by
librarian-bot
Why is this model significantly bigger than microsoft/deberta-v3-large
#3 opened over 2 years ago
by
cyenjoylife
Minimal reproducible inference code please
1
#2 opened almost 3 years ago
by
BornSaint