Instructions to use BM-K/KoDiffCSE-RoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BM-K/KoDiffCSE-RoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BM-K/KoDiffCSE-RoBERTa")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BM-K/KoDiffCSE-RoBERTa") model = AutoModel.from_pretrained("BM-K/KoDiffCSE-RoBERTa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e379e0fe07ef82980538125130a0da384f0003dabaf809fba2cfefd12c5cc4e8
- Size of remote file:
- 443 MB
- SHA256:
- 163b7fcace7c7eb562226596ddbd006f1443402387ab38cf7705f7774eaf6957
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