Instructions to use hebashakeel/roberta-wellness-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hebashakeel/roberta-wellness-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hebashakeel/roberta-wellness-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hebashakeel/roberta-wellness-classifier") model = AutoModelForSequenceClassification.from_pretrained("hebashakeel/roberta-wellness-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bece030ac00a867b3debb278aa8a3d351f653ca667cfcdee02a839d2026e16ee
- Size of remote file:
- 5.24 kB
- SHA256:
- b4567a8d1322130faf4972fea92a8cc9abd2f9a53c3bb0eef3c5a2a4056079ff
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