Zero-Shot Classification
Transformers
PyTorch
Safetensors
xlm-roberta
text-classification
Zero-Shot Classification
Instructions to use DAMO-NLP-SG/zero-shot-classify-SSTuning-XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DAMO-NLP-SG/zero-shot-classify-SSTuning-XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="DAMO-NLP-SG/zero-shot-classify-SSTuning-XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DAMO-NLP-SG/zero-shot-classify-SSTuning-XLM-R") model = AutoModelForSequenceClassification.from_pretrained("DAMO-NLP-SG/zero-shot-classify-SSTuning-XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5252de3b893f12132c41972468d46a0a61a8a89fa3edf1a811f3ac386be1520f
- Size of remote file:
- 1.11 GB
- SHA256:
- f64dbc9232b5e31fdde962a352f699bc1ebb1ed4bf3da230511785c9ca36fbd9
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