Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Jios/bert-unformatted-network-data-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jios/bert-unformatted-network-data-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jios/bert-unformatted-network-data-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jios/bert-unformatted-network-data-test") model = AutoModelForSequenceClassification.from_pretrained("Jios/bert-unformatted-network-data-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# EXAMPLE FULL NAMES:
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label_0 =
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1. malicious from training dataset
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2. benign from training dataset
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# EXAMPLE FULL NAMES:
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label_0 = malicious (UDP-lag DDoS), label_1 = benign
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1. malicious from training dataset
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2. benign from training dataset
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