Instructions to use researchaccount/sa_sub3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use researchaccount/sa_sub3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="researchaccount/sa_sub3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("researchaccount/sa_sub3") model = AutoModelForSequenceClassification.from_pretrained("researchaccount/sa_sub3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57478e9eeafbaebe45d7a2642c6b7dce76c780e0425de39c62df7faadfc419d4
- Size of remote file:
- 651 MB
- SHA256:
- 7ac66033b46baeb52533cebad860cef16cc207f8d05006dcef1371130a837499
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