Instructions to use BM-K/KoSimCSE-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BM-K/KoSimCSE-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BM-K/KoSimCSE-roberta")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BM-K/KoSimCSE-roberta") model = AutoModel.from_pretrained("BM-K/KoSimCSE-roberta") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5367774b8300f4bee18202753074c5dc9edbe46d85bac2795c953cb2d9011369
- Size of remote file:
- 443 MB
- SHA256:
- 9941030acf7c0e0da0560d26ca00b97b701d4d737946611165e4d106cdf5c476
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