Instructions to use BM-K/KoSimCSE-Unsup-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BM-K/KoSimCSE-Unsup-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BM-K/KoSimCSE-Unsup-BERT")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BM-K/KoSimCSE-Unsup-BERT") model = AutoModel.from_pretrained("BM-K/KoSimCSE-Unsup-BERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ed100ad1cb3002256b4a301b951d11cbbb3350b3323db482ec485bcf2c3ac57
- Size of remote file:
- 443 MB
- SHA256:
- e1464e90dfaf393afc63e48dafd3db5ec46c75d83903fb1669aef654ff32da3a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.