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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BM-K/KoSimCSE-Unsup-BERT: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/BM-K/KoSimCSE-Unsup-BERT/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://BM-K/KoSimCSE-Unsup-BERT@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BM-K/KoSimCSE-Unsup-BERT/resolve/refs%2Fpr%2F1/pytorch_model.bin
443 MB
- Xet hash:
- 6ed100ad1cb3002256b4a301b951d11cbbb3350b3323db482ec485bcf2c3ac57
- Size of remote file:
- 443 MB
- SHA256:
- e1464e90dfaf393afc63e48dafd3db5ec46c75d83903fb1669aef654ff32da3a
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