Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ai-ar/simple-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai-ar/simple-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ai-ar/simple-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ai-ar/simple-classification") model = AutoModelForSequenceClassification.from_pretrained("ai-ar/simple-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34f6dca46fd8ed35716dbe0c847773383fdb198d1c20550b3a43bccbcfd2ee6d
- Size of remote file:
- 268 MB
- SHA256:
- 3f4b42871ef2f3e2c9add391524428cb2d0e11a2fc15d9b89cabae1a8858ff7c
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