Instructions to use researchaccount/sa_sub1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use researchaccount/sa_sub1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="researchaccount/sa_sub1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("researchaccount/sa_sub1") model = AutoModelForSequenceClassification.from_pretrained("researchaccount/sa_sub1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2de8a180ba46b6faf2937a926362f08b0d7a5a4fbf5cf62980c1cc862b616666
- Size of remote file:
- 651 MB
- SHA256:
- 620b2fd192b10e01bf36414d9d063fce436f55f614d78e0c10d8cfeaeea08dfe
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