Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v3-base
deberta-v3
deberta
nli
natural-language-inference
multitask
multi-task
pipeline
extreme-multi-task
extreme-mtl
tasksource
zero-shot
rlhf
Eval Results (legacy)
Instructions to use sileod/deberta-v3-base-tasksource-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sileod/deberta-v3-base-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-base-tasksource-nli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sileod/deberta-v3-base-tasksource-nli") model = AutoModelForSequenceClassification.from_pretrained("sileod/deberta-v3-base-tasksource-nli") - Inference
- Notebooks
- Google Colab
- Kaggle
How to train the model?
#10 opened 10 months ago
by
Phase-Technologies
Librarian Bot: Update Hugging Face dataset ID
#8 opened about 2 years ago
by
librarian-bot
fINER Error
7
#7 opened over 2 years ago
by
iampoppyxx
onnxruntime error
6
#6 opened over 2 years ago
by
gsasikiran
Is there a Quantized version(s)?
2
#5 opened over 2 years ago
by
mrmikelevy
Different results than Inference API
5
#4 opened almost 3 years ago
by
nlpsingh
Which datasets are included in the NLI training data / NLI head?
8
#3 opened almost 3 years ago
by
MoritzLaurer