Instructions to use namin0202/pna-simcse-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namin0202/pna-simcse-bert-base-uncased with Transformers:
# Load model directly from transformers import AutoTokenizer, BertForCL tokenizer = AutoTokenizer.from_pretrained("namin0202/pna-simcse-bert-base-uncased") model = BertForCL.from_pretrained("namin0202/pna-simcse-bert-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f4e3503ae1931d0de0218b8a4fba13be2e24e37f53c3f8d8262934b20b0222d
- Size of remote file:
- 438 MB
- SHA256:
- 16c5d3e54a49ce0c6c0a382525355ba9a6a5db0f9cb504bd1421ec54ed7a4eb3
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