Text Classification
Transformers
Safetensors
Indonesian
gemma2
spam-detection
indonesian
chatbot
security
Instructions to use nahiar/spam-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nahiar/spam-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nahiar/spam-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nahiar/spam-analysis") model = AutoModelForSequenceClassification.from_pretrained("nahiar/spam-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 283cda0a7131aaea06d3e6157cbbbde4ab1af5df668d2078b8d023ade2ae24e7
- Size of remote file:
- 17.5 MB
- SHA256:
- 33457e136a33f1080fe73a484d1752e633748cec558ff8c15b79a4e08b96bad8
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