Instructions to use Cournane/roberta-base-labels-Neckline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-labels-Neckline with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-labels-Neckline")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-labels-Neckline") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-labels-Neckline") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94f5c3e8bd4ead583b149200828b72b3c7d7e8922f9713897277ef6c0af75e70
- Size of remote file:
- 3.9 kB
- SHA256:
- 9228434965a05f27cefd63b1d137bc1e55dc3e10ad90c60395e18b85e8e4ff31
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