Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Sharpaxis/distilbert-sensitive-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharpaxis/distilbert-sensitive-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sharpaxis/distilbert-sensitive-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sharpaxis/distilbert-sensitive-classification") model = AutoModelForSequenceClassification.from_pretrained("Sharpaxis/distilbert-sensitive-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df712832d5a3f3fc1375da2483df44fa3d1134b18fe9f60afc6a637e8440b0d5
- Size of remote file:
- 5.37 kB
- SHA256:
- 732f29cbf8205d5fd995a99dffe890678a5fb7b35def56d557bb6f282364bb69
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