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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc4b3e60060dc98df41433c7bdf23b1f45b66685eeece33994816122457ac428
- Size of remote file:
- 2.93 kB
- SHA256:
- c4ef45588b98ee4ba395f9b88a031be7a5cdda64e25e3b6bf85dd70623d9274f
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