Instructions to use WENGSYX/Multilingual_SimCSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WENGSYX/Multilingual_SimCSE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="WENGSYX/Multilingual_SimCSE")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("WENGSYX/Multilingual_SimCSE") model = AutoModel.from_pretrained("WENGSYX/Multilingual_SimCSE") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 673266024541a4e5d6666044777424fb0e3ec9d08ee6922f0465976681549297
- Size of remote file:
- 1.11 GB
- SHA256:
- 340ca56b68763d795d5e731ac271653655c9b0b01410febd1ae2fb95ff3416da
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