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:
- 257afbbaf34cc2cbc36be64126f7415ca3b2da9c289c39125ce054a0789bc525
- Size of remote file:
- 4.09 kB
- SHA256:
- a8540d8113c2c3fa350780ff36a1a7d55e760de16cf910dbbfcf189ed63547db
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