Instructions to use driftbench/stsb_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use driftbench/stsb_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="driftbench/stsb_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("driftbench/stsb_base") model = AutoModelForSequenceClassification.from_pretrained("driftbench/stsb_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 657b58545f9e146d93883d46d36ebd508b874362d900ea00742764b3c8e620ba
- Size of remote file:
- 3.52 kB
- SHA256:
- 1a5042330565df394509f070fc44e9dd4634cdb6765f964f0448eb19ada1ee41
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