Instructions to use ncsu-dk-lab/AutoDisProxyT-STSB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ncsu-dk-lab/AutoDisProxyT-STSB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ncsu-dk-lab/AutoDisProxyT-STSB")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ncsu-dk-lab/AutoDisProxyT-STSB") model = AutoModelForSequenceClassification.from_pretrained("ncsu-dk-lab/AutoDisProxyT-STSB") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2307c9d85b8d6fa1d9108a72c20fc39f3b42d73996e4d3c929cc6ec75897e1a3
- Size of remote file:
- 34.3 MB
- SHA256:
- dd2392d68ba15911e69c429109e06a5b13b3cae51981bd4cb24f0a2677f8603a
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