Text Classification
Transformers
Safetensors
PyTorch
English
tiny_log_classifier
cybersecurity
blue-team
log-analysis
custom-code
custom_code
Instructions to use mozarilla/tiny-blue-log-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mozarilla/tiny-blue-log-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mozarilla/tiny-blue-log-classifier", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("mozarilla/tiny-blue-log-classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 517 Bytes
12097aa | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"architectures": [
"TinyLogForSequenceClassification"
],
"auto_map": {
"AutoConfig": "configuration_tiny_log.TinyLogConfig",
"AutoModelForSequenceClassification": "modeling_tiny_log.TinyLogForSequenceClassification"
},
"hidden_size": 16,
"id2label": {
"0": "BENIGN",
"1": "SUSPICIOUS"
},
"label2id": {
"BENIGN": 0,
"SUSPICIOUS": 1
},
"max_position_embeddings": 96,
"model_type": "tiny_log_classifier",
"num_labels": 2,
"pad_token_id": 0,
"vocab_size": 1024
}
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