Instructions to use abletobetable/stress_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abletobetable/stress_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abletobetable/stress_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abletobetable/stress_bert") model = AutoModelForSequenceClassification.from_pretrained("abletobetable/stress_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1946d755577ebd151719be4568d461f74f9dc69b0402b0c8e4a5437fb95203d7
- Size of remote file:
- 19.5 MB
- SHA256:
- 9b490a32ea2165bacfe84b9881dfc4856b26901068b17f10aa6444f7d88dfd1b
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