Instructions to use gcyzsl/sup-VisualCSE-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gcyzsl/sup-VisualCSE-bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="gcyzsl/sup-VisualCSE-bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gcyzsl/sup-VisualCSE-bert-base-uncased") model = AutoModel.from_pretrained("gcyzsl/sup-VisualCSE-bert-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d1f5a571f29428bc61764f12b5f4113221e6ac5d73e1a3285734e6fd2d3f260
- Size of remote file:
- 443 MB
- SHA256:
- 73129720f20b2fb4e0444bf11cf84a855f7e78d3508402775664ab6385e9fe1f
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