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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (cf9db26f3667b25d44eb177ebe5a3b1835e71957) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>8e8aa4d
-
Update README.md
d66431a
-
Update README.md
1265437 -
Update README.md
94278f8 -
Update README.md
7aa7155 -
Update README.md
a6d9f34 -
Update README.md
18fe2bd -
Update README.md
06eeb42 -
Update README.md
cbb8b05 -
Update README.md
a3e920f -
Update README.md
29633e7 -
Initial upload
2a87f9d -
initial commit
04ed53a