Instructions to use Nma/RuleClassify-Textclassify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nma/RuleClassify-Textclassify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Nma/RuleClassify-Textclassify")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Nma/RuleClassify-Textclassify") model = AutoModelForSequenceClassification.from_pretrained("Nma/RuleClassify-Textclassify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (26ba0a329451736f9031f3e1a3ec57ce5999c99b) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>8fb89c0
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First Commit
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initial commit
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