Instructions to use victoriapl01/sensitive_spanish_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use victoriapl01/sensitive_spanish_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="victoriapl01/sensitive_spanish_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("victoriapl01/sensitive_spanish_classifier") model = AutoModelForSequenceClassification.from_pretrained("victoriapl01/sensitive_spanish_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from victoriapl01/sensitive_spanish_classifier: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/victoriapl01/sensitive_spanish_classifier/resolve/main/optimizer.pt
- Command line
-
hf download hf://victoriapl01/sensitive_spanish_classifier/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/victoriapl01/sensitive_spanish_classifier/resolve/main/optimizer.pt
997 MB
- Xet hash:
- 7c75d0a16b8260861d1364952335381378e0252af5fa5525293a56540e9c70c3
- Size of remote file:
- 997 MB
- SHA256:
- 1ba42574bbca99656e10cfe011a823fbef4fe5f69cfa15c15d2ed38b3ae01306
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