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:
- 54918d65f3b2877736671298851fee413dce9cbaa30ffa02e27c5e32b7211832
- Size of remote file:
- 438 MB
- SHA256:
- 99a426d8487002df8623f33011771fe7fb759da0271cd42673303c4c6ae047fb
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