Text Classification
Transformers
Safetensors
Urdu
xlm-roberta
spam-detection
urdu
nlp
text-embeddings-inference
Instructions to use hamza-amin/urdu-spam-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hamza-amin/urdu-spam-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hamza-amin/urdu-spam-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hamza-amin/urdu-spam-classifier") model = AutoModelForSequenceClassification.from_pretrained("hamza-amin/urdu-spam-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14a0575d5ff3b8b96f0a18b75c040f0abafaa703fb2ddd431fc53821e7d5f186
- Size of remote file:
- 16.8 MB
- SHA256:
- 7a0a4368a5855b54c683bd4023699ff519493e5e948f4dbee947b02762139fe4
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