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:
- 31cfad7e457e392bdebe2bd63796205ff3f6ab825e13da0a03d83dfbf932c919
- Size of remote file:
- 17.1 MB
- SHA256:
- 62c24cdc13d4c9952d63718d6c9fa4c287974249e16b7ade6d5a85e7bbb75626
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