Text Classification
Transformers
PyTorch
Safetensors
Russian
deberta
spam-detection
russian
Eval Results (legacy)
Instructions to use RUSpam/spam_deberta_v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RUSpam/spam_deberta_v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RUSpam/spam_deberta_v4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RUSpam/spam_deberta_v4") model = AutoModelForSequenceClassification.from_pretrained("RUSpam/spam_deberta_v4") - Notebooks
- Google Colab
- Kaggle
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# Цитирование
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```
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@MISC{
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author = {
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title = {Russian Spam Classification Model},
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url = {https://huggingface.co/
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year = 2024
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}
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```
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# Цитирование
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```
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@MISC{NeuroSpaceX/ruSpamNS_v7,
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author = {Kirill Fedko (NeuroSpaceX), Andrey Tolstóy},
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title = {Russian Spam Classification Model},
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url = {https://huggingface.co/NeuroSpaceX/ruSpamNS_v7},
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year = 2024
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}
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```
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