Feature Extraction
Transformers
Safetensors
English
deberta-v2
embedding
scientific
abstract
text-embeddings-inference
Instructions to use CLAUSE-Bielefeld/SemCSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLAUSE-Bielefeld/SemCSE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="CLAUSE-Bielefeld/SemCSE")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("CLAUSE-Bielefeld/SemCSE") model = AutoModel.from_pretrained("CLAUSE-Bielefeld/SemCSE") - Notebooks
- Google Colab
- Kaggle
Ctrl+K