Instructions to use researchaccount/sa_sub5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use researchaccount/sa_sub5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="researchaccount/sa_sub5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("researchaccount/sa_sub5") model = AutoModelForSequenceClassification.from_pretrained("researchaccount/sa_sub5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc27cd2b5bce25c8efe953886eb4835a519e5511e592fb68c8b894bc78ae14e8
- Size of remote file:
- 651 MB
- SHA256:
- 17101e84ebb1875d68587df456e5cf3f11d13981684e3470d311ef869c746509
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