Instructions to use Cournane/roberta-base-labels-Upper_fabric with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-labels-Upper_fabric with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-labels-Upper_fabric")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-labels-Upper_fabric") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-labels-Upper_fabric") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e93930ec3f796e3acb1fe481a87890e8edbde222011df5b8dcab338f3d284569
- Size of remote file:
- 3.9 kB
- SHA256:
- d42663bfe259b1b56cb15cfe3d690df631be23063611931f552d75b43f6ea46c
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