Instructions to use Cournane/roberta-base-labels-Lower_fabric with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-labels-Lower_fabric with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-labels-Lower_fabric", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-labels-Lower_fabric") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-labels-Lower_fabric", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b801a5034c181ba15fba26b0e5d1b064534edfe5171cdcf6275cdfd9a834a08
- Size of remote file:
- 3.9 kB
- SHA256:
- dfe1bb132295c4f13e776ae238ba662862c3e7e04e684d92937e8f00ea6ea7fa
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