Instructions to use Cournane/roberta-base-labels-Socks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-labels-Socks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-labels-Socks")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-labels-Socks") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-labels-Socks") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c861a43171ecf4de9bfd56bc49c0104c3d79b57e29adcdf354ea36f1d63e615
- Size of remote file:
- 499 MB
- SHA256:
- e5ed11ddbf8e25dd5f16b33ffce8b89895d548ff4be538565999cba226a0bba5
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