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:
- 31ac37ce1ba133858e842c6a63e618bb7917b486f1fcaf0136ebe9a6593ab129
- Size of remote file:
- 499 MB
- SHA256:
- 7755e2ffd425950fce5b2951360a322e625042dad8f3577b80a0f75d93eeccf9
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