Instructions to use ModelTC/bert-base-uncased-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bert-base-uncased-stsb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bert-base-uncased-stsb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bert-base-uncased-stsb") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bert-base-uncased-stsb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf166d34ba87aa01fc4ce6828501a538fd181d739001026a098e70b7a15a1cd0
- Size of remote file:
- 14.7 kB
- SHA256:
- f3a7c8a4c63ab300071a77268a406ee50547f5793c538dcde70593def84c9ed8
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