Instructions to use SparkBeyond/roberta-large-sts-b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SparkBeyond/roberta-large-sts-b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SparkBeyond/roberta-large-sts-b")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SparkBeyond/roberta-large-sts-b") model = AutoModelForSequenceClassification.from_pretrained("SparkBeyond/roberta-large-sts-b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 992b936a33ce5605ac84252298989a00b3e16fffbf1925bafba24a8b4437bb04
- Size of remote file:
- 1.42 GB
- SHA256:
- 0fd60c2313079cd7c177082b9b12a36125318fd5d4f92608041b43e32c2314ae
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